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Live Discussion on Startups, AI, and Career Growth
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Aug 6, 2025
Join us live on July 21 for an exclusive C# Corner Webinar featuring an in-depth discussion on Startups, Artificial Intelligence, and Career Growth. Learn from industry experts as they share real-world insights, strategies, and personal journeys to help you navigate the future of tech and entrepreneurship. Agenda: • Building from Scratch – Insights on launching a successful startup, from ideation to execution. • Navigating Career Paths – How to transition between roles, industries, or entrepreneurship. • Networking & Mentorship – The role of connections in accelerating startup success and career growth. • Scaling & Sustainability – Strategies for growing your startup while maintaining work-life balance. • Funding & Monetization – Understanding investment options, bootstrapping, and revenue models. • AI & Innovation – Exploring how AI is transforming industries, enhancing productivity, and opening new avenues for startups and professionals alike. • Learn practical ways to leverage AI in your products, services, and career journey. Note: This event is exclusively for students of St. Joseph’s Engineering College, Chennai. 📺 CSharp TV - Dev Streaming Destination http://csharp.tv 🌎 C# Corner - Community of Software and Data Developers https://www.c-sharpcorner.com
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[Music] feel.
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feel.
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feel. Feeling
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it.
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Do it. Do it.
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[Music]
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Do it.
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Do it. Do it. Do it. Do it. Do it.
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Do it. Do it.
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Do it. Do it.
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Do it. Do it.
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Do it. Do it. [Music]
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[Music] Do it. Do it.
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Do it.
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Feeling
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Feeling [Music]
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[Music] feeling
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feeling
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feeling
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feeling [Music]
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[Music] feeling.
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Do it. Do it.
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Do it. Do it.
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Do it.
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Do it. Do it.
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Do it. Do it.
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Do it. Do it. [Music]
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Do it. Do it.
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[Music]
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Everywhere you feel.
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Everywhere you feel.
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Everywhere you feel. [Music]
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Heat. Heat. N.
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Heat. Heat. N.
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Hello and good Morning. I hope um
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Hello and good Morning. I hope um
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Hello and good Morning. I hope um everyone can hear me. It's really hard
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everyone can hear me. It's really hard
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everyone can hear me. It's really hard to tell right now because I can't see
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to tell right now because I can't see
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to tell right now because I can't see the screen.
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Everyone, welcome to the show.
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Everyone, welcome to the show.
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Everyone, welcome to the show. Um at let me know when you're good to
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Um at let me know when you're good to
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Um at let me know when you're good to go.
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Okay, let's see.
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Okay, let's see.
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Okay, let's see. This is um
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This is um
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This is um Okay, we're good to go everybody.
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Okay, we're good to go everybody.
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Okay, we're good to go everybody. Good morning all. It is nice to meet
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Good morning all. It is nice to meet
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Good morning all. It is nice to meet you. My name is Mahesh Shan and today we
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you. My name is Mahesh Shan and today we
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you. My name is Mahesh Shan and today we are going to talk about some of the new
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are going to talk about some of the new
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are going to talk about some of the new technologies, talk about your career
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technologies, talk about your career
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technologies, talk about your career path,
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path,
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path, talk about what is something you should
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talk about what is something you should
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talk about what is something you should be learning, where the industry is going
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be learning, where the industry is going
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be learning, where the industry is going and um
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and um
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and um end of the day goal is that you learn
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end of the day goal is that you learn
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end of the day goal is that you learn something useful, something useful that
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something useful, something useful that
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something useful, something useful that can help you get a job, get in the
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can help you get a job, get in the
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can help you get a job, get in the industry. If you are trying to start
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industry. If you are trying to start
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industry. If you are trying to start your own startup, you can get some ideas
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your own startup, you can get some ideas
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your own startup, you can get some ideas and some help. So, let's get started.
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and some help. So, let's get started.
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and some help. So, let's get started. Um,
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let me make the screen bigger. There you
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let me make the screen bigger. There you
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let me make the screen bigger. There you go.
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My name is Mahes Chan. A little
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My name is Mahes Chan. A little
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My name is Mahes Chan. A little background. I'm a founder of Corner.
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background. I'm a founder of Corner.
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background. I'm a founder of Corner. This show is brought to you by Corner.
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This show is brought to you by Corner.
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This show is brought to you by Corner. I'm sure you guys
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I'm sure you guys
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I'm sure you guys uh had amazing day at Hack India. Hack
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uh had amazing day at Hack India. Hack
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uh had amazing day at Hack India. Hack India is one of the initiatives from C#
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India is one of the initiatives from C#
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India is one of the initiatives from C# Corner.
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Corner.
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Corner. Um
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Um
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Um when I was your age,
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when I was your age,
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when I was your age, I didn't know really where to start, how
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I didn't know really where to start, how
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I didn't know really where to start, how to start. So that's the reason we do
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to start. So that's the reason we do
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to start. So that's the reason we do these shows and this live webinars
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these shows and this live webinars
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these shows and this live webinars because
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because
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because so you can get ahead and learn
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so you can get ahead and learn
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so you can get ahead and learn from uh my experience.
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from uh my experience.
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from uh my experience. So this talk is very important in the
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So this talk is very important in the
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So this talk is very important in the sense that the tech is booming and uh
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sense that the tech is booming and uh
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sense that the tech is booming and uh with AI lot of things are changing
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with AI lot of things are changing
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with AI lot of things are changing things are changing at a faster pace
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things are changing at a faster pace
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things are changing at a faster pace that we can't catch up we can't keep up
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that we can't catch up we can't keep up
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that we can't catch up we can't keep up to. So that is why
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to. So that is why
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to. So that is why if you are a student, you're in a
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if you are a student, you're in a
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if you are a student, you're in a college,
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college,
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college, you have to pay attention because if you
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you have to pay attention because if you
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you have to pay attention because if you don't, things are moving so fast you
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don't, things are moving so fast you
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don't, things are moving so fast you will miss something.
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will miss something.
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will miss something. So in today's talk, we will talk about
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So in today's talk, we will talk about
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So in today's talk, we will talk about AI, we'll talk about startups,
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AI, we'll talk about startups,
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AI, we'll talk about startups, but end of the day, I want to take some
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but end of the day, I want to take some
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but end of the day, I want to take some of your questions. So if you guys can
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of your questions. So if you guys can
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of your questions. So if you guys can have your questions ready, you can type
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have your questions ready, you can type
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have your questions ready, you can type your questions in the end of the show
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your questions in the end of the show
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your questions in the end of the show and then we will run through those.
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So if you look at top
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So if you look at top
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So if you look at top technologies right now, when you think
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technologies right now, when you think
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technologies right now, when you think of what companies are hiring for, if uh
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of what companies are hiring for, if uh
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of what companies are hiring for, if uh if you go to a company tech company and
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if you go to a company tech company and
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if you go to a company tech company and you look at some of the jobs, what are
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you look at some of the jobs, what are
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you look at some of the jobs, what are they hiring for? These are some of the
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they hiring for? These are some of the
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they hiring for? These are some of the top demands in coming time today and
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top demands in coming time today and
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top demands in coming time today and also in coming time. So from now till
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also in coming time. So from now till
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also in coming time. So from now till next few years these demands will be
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next few years these demands will be
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next few years these demands will be there. So start with AI and machine
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there. So start with AI and machine
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there. So start with AI and machine learning.
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learning.
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learning. So anybody who's doing AI and machine
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So anybody who's doing AI and machine
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So anybody who's doing AI and machine learning
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learning
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learning they will be in demand. This is growing.
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they will be in demand. This is growing.
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they will be in demand. This is growing. Python for example, Python machine
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Python for example, Python machine
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Python for example, Python machine learning libraries,
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learning libraries,
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learning libraries, models, LLMs, all those come in that AI
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models, LLMs, all those come in that AI
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models, LLMs, all those come in that AI and machine learning track.
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and machine learning track.
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and machine learning track. Another
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Another
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Another growing job is the cyber security. When
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growing job is the cyber security. When
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growing job is the cyber security. When AI is growing, AI is also going to
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AI is growing, AI is also going to
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AI is growing, AI is also going to create a lot of problems. It has already
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create a lot of problems. It has already
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create a lot of problems. It has already created a lot of problems. It's already
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created a lot of problems. It's already
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created a lot of problems. It's already creating more problems.
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creating more problems.
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creating more problems. And uh cyber security is going to be in
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And uh cyber security is going to be in
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And uh cyber security is going to be in big demand as well. So if you are
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big demand as well. So if you are
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big demand as well. So if you are somebody who likes to go into the
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somebody who likes to go into the
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somebody who likes to go into the security route, you want to start
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security route, you want to start
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security route, you want to start looking into cyber security
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looking into cyber security
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looking into cyber security and cyber security has you know multiple
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and cyber security has you know multiple
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and cyber security has you know multiple tracks. There are some advanced they're
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tracks. There are some advanced they're
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tracks. There are some advanced they're not not so advanced.
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The third cloud and devops engineer that
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The third cloud and devops engineer that
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The third cloud and devops engineer that will continue to grow. Cloud is
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will continue to grow. Cloud is
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will continue to grow. Cloud is everything is moving to cloud. It has
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everything is moving to cloud. It has
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everything is moving to cloud. It has already moved to cloud. So cloud devops
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already moved to cloud. So cloud devops
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already moved to cloud. So cloud devops engineer, cloud architects, Azure cloud,
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engineer, cloud architects, Azure cloud,
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engineer, cloud architects, Azure cloud, AWS, they will also be in demand. Data
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AWS, they will also be in demand. Data
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AWS, they will also be in demand. Data scientist of course data is the key.
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scientist of course data is the key.
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scientist of course data is the key. Data is the main thing behind AI. So
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Data is the main thing behind AI. So
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Data is the main thing behind AI. So data scientists will always be in demand
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data scientists will always be in demand
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data scientists will always be in demand for next few years.
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for next few years.
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for next few years. And then there's a new job coming out is
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And then there's a new job coming out is
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And then there's a new job coming out is prompt engineering. And this is very
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prompt engineering. And this is very
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prompt engineering. And this is very interesting job. It's not really
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interesting job. It's not really
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interesting job. It's not really engineering to be honest. is just a and
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engineering to be honest. is just a and
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engineering to be honest. is just a and I'll talk a little bit more about this
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I'll talk a little bit more about this
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I'll talk a little bit more about this prompt engineering a little in my next
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prompt engineering a little in my next
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prompt engineering a little in my next slides but this is another job that's in
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slides but this is another job that's in
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slides but this is another job that's in high demand prompt engineering is
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high demand prompt engineering is
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high demand prompt engineering is something which I would say everybody
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something which I would say everybody
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something which I would say everybody should know everybody should master
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should know everybody should master
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should know everybody should master prompt engineering because even though
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prompt engineering because even though
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prompt engineering because even though you're not going for a job you are at
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you're not going for a job you are at
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you're not going for a job you are at home you are doing your
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home you are doing your
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home you are doing your um you working your own things you will
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um you working your own things you will
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um you working your own things you will prompt engineering something you will
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prompt engineering something you will
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prompt engineering something you will need now coming more than anything else.
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need now coming more than anything else.
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need now coming more than anything else. Anytime you work with Chad GPT or any of
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Anytime you work with Chad GPT or any of
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Anytime you work with Chad GPT or any of these AI tools, prompting is the key and
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these AI tools, prompting is the key and
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these AI tools, prompting is the key and becoming a prompt engineer is very
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becoming a prompt engineer is very
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becoming a prompt engineer is very important and you can be a prompt
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important and you can be a prompt
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important and you can be a prompt engineer as well as something else.
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engineer as well as something else.
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engineer as well as something else. Prompt engineering something you can do
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Prompt engineering something you can do
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Prompt engineering something you can do side by side. It's not a big work. It's
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side by side. It's not a big work. It's
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side by side. It's not a big work. It's not a lot of work. It's literally in
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not a lot of work. It's literally in
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not a lot of work. It's literally in couple of weeks you can become a prompt
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couple of weeks you can become a prompt
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couple of weeks you can become a prompt engineer.
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engineer.
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engineer. And then fullstack developer obviously
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And then fullstack developer obviously
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And then fullstack developer obviously that's always has been in demand for a
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that's always has been in demand for a
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that's always has been in demand for a while. It will always be in demand.
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while. It will always be in demand.
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while. It will always be in demand. Fullstack developer means when you can
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Fullstack developer means when you can
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Fullstack developer means when you can build entire application from front end
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build entire application from front end
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build entire application from front end to back end to middle middle layer and
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to back end to middle middle layer and
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to back end to middle middle layer and also do deploy and everything else.
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also do deploy and everything else.
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also do deploy and everything else. Vibe coder is a new term. This is a
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Vibe coder is a new term. This is a
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Vibe coder is a new term. This is a another new job comb
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another new job comb
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another new job comb coder and prompt engineer. Vcoder is you
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coder and prompt engineer. Vcoder is you
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coder and prompt engineer. Vcoder is you become a
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become a
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become a software developer who build
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software developer who build
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software developer who build applications using AI tools and and just
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applications using AI tools and and just
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applications using AI tools and and just w tools. You don't really write code but
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w tools. You don't really write code but
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w tools. You don't really write code but you can build applications. For example,
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you can build applications. For example,
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you can build applications. For example, today you can go online. And I'm sure
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today you can go online. And I'm sure
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today you can go online. And I'm sure many of you guys already using it. You
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many of you guys already using it. You
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many of you guys already using it. You go online and go to these tools you know
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go online and go to these tools you know
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go online and go to these tools you know vzero
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vzero
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vzero or loveable even cursor all these tools
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or loveable even cursor all these tools
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or loveable even cursor all these tools are there out there. You can just go and
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are there out there. You can just go and
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are there out there. You can just go and type few prompts and you can create your
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type few prompts and you can create your
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type few prompts and you can create your full application there. That is growing
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full application there. That is growing
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full application there. That is growing in big demand. Actually I was in New
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in big demand. Actually I was in New
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in big demand. Actually I was in New York two weeks ago
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York two weeks ago
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York two weeks ago and there are more and more hiring
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and there are more and more hiring
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and there are more and more hiring happening for vibe coders
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happening for vibe coders
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happening for vibe coders than anything else. So that will also be
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than anything else. So that will also be
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than anything else. So that will also be in big demand.
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in big demand.
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in big demand. It's good to know that it's good that
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It's good to know that it's good that
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It's good to know that it's good that you guys learning the fundamentals the
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you guys learning the fundamentals the
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you guys learning the fundamentals the data you know the basics of everything
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data you know the basics of everything
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data you know the basics of everything but knowing these prompt engineering and
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but knowing these prompt engineering and
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but knowing these prompt engineering and vibe coding those are the two demands
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vibe coding those are the two demands
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vibe coding those are the two demands they're growing faster. If any companies
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they're growing faster. If any companies
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they're growing faster. If any companies hiring young generation
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hiring young generation
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hiring young generation they expect that to be I expect that you
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they expect that to be I expect that you
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they expect that to be I expect that you to be you know really good at these two
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to be you know really good at these two
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to be you know really good at these two things and then you know there's last is
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things and then you know there's last is
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things and then you know there's last is blockchain web3 developer blockchain web
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blockchain web3 developer blockchain web
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blockchain web3 developer blockchain web 3 developer will grow more in coming
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3 developer will grow more in coming
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3 developer will grow more in coming time it's there's not too many jobs
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time it's there's not too many jobs
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time it's there's not too many jobs opening right now but if you are
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opening right now but if you are
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opening right now but if you are somebody say you know what I want to get
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somebody say you know what I want to get
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somebody say you know what I want to get into web 3 because that's my interest
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into web 3 because that's my interest
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into web 3 because that's my interest you know cryptocurrencies and all that
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you know cryptocurrencies and all that
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you know cryptocurrencies and all that that new technologies coming out if
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that new technologies coming out if
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that new technologies coming out if that's your interest you can also go
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that's your interest you can also go
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that's your interest you can also go into blockchain and web3 space so that
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into blockchain and web3 space so that
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into blockchain and web3 space so that will be that demand will grow in coming
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will be that demand will grow in coming
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will be that demand will grow in coming time
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time
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time so so far if you guys want to know that
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so so far if you guys want to know that
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so so far if you guys want to know that what should I learn today so my future
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what should I learn today so my future
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what should I learn today so my future career is safe I have jobs I have I'm in
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career is safe I have jobs I have I'm in
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career is safe I have jobs I have I'm in demand these are the some of the
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demand these are the some of the
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demand these are the some of the technologies you want to start thinking
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technologies you want to start thinking
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technologies you want to start thinking about these are some of the roles but if
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about these are some of the roles but if
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about these are some of the roles but if I have to pick two of them right now
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I have to pick two of them right now
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I have to pick two of them right now three of them that'll be AI machine
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three of them that'll be AI machine
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three of them that'll be AI machine learning prompt engineer vive coder
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learning prompt engineer vive coder
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learning prompt engineer vive coder prompt engineer and vive coder are
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prompt engineer and vive coder are
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prompt engineer and vive coder are something you can do side by side with
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something you can do side by side with
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something you can do side by side with anything else for example you can be a
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anything else for example you can be a
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anything else for example you can be a fullstack developer and also vive coder
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fullstack developer and also vive coder
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fullstack developer and also vive coder and prompt engineer right you can be a
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and prompt engineer right you can be a
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and prompt engineer right you can be a um cyber security analyst and you can
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um cyber security analyst and you can
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um cyber security analyst and you can also be a prompt engineer in v coder so
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also be a prompt engineer in v coder so
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also be a prompt engineer in v coder so I would say everybody should go and
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I would say everybody should go and
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I would say everybody should go and learn prompt engineering and vive
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learn prompt engineering and vive
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learn prompt engineering and vive coding. Those are the two skills and
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coding. Those are the two skills and
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coding. Those are the two skills and they're for everybody. They are for
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they're for everybody. They are for
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they're for everybody. They are for teachers. They are for my me myself. I'm
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teachers. They are for my me myself. I'm
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teachers. They are for my me myself. I'm doing vive coding all the time these
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doing vive coding all the time these
14:33
doing vive coding all the time these days. I'm doing prompt engineering all
14:35
days. I'm doing prompt engineering all
14:35
days. I'm doing prompt engineering all the time these days. So they are for
14:37
the time these days. So they are for
14:37
the time these days. So they are for anybody. For example, if you have an
14:40
anybody. For example, if you have an
14:40
anybody. For example, if you have an idea
14:41
idea
14:41
idea and you say, you know what, I want to
14:43
and you say, you know what, I want to
14:43
and you say, you know what, I want to build something. I want to, you know,
14:47
build something. I want to, you know,
14:47
build something. I want to, you know, try something. I want to build P. I want
14:49
try something. I want to build P. I want
14:49
try something. I want to build P. I want to launch my app. I want my website, you
14:51
to launch my app. I want my website, you
14:51
to launch my app. I want my website, you can just go and start doing it tomorrow
14:53
can just go and start doing it tomorrow
14:53
can just go and start doing it tomorrow and boom, you'll be you'll be done in in
14:55
and boom, you'll be you'll be done in in
14:55
and boom, you'll be you'll be done in in hours. The advantage of these is is you
14:59
hours. The advantage of these is is you
14:59
hours. The advantage of these is is you just get things faster, right? So, we'll
15:03
just get things faster, right? So, we'll
15:03
just get things faster, right? So, we'll talk more in this coming slides.
15:07
So, out of all those as I said out of
15:10
So, out of all those as I said out of
15:10
So, out of all those as I said out of all those skills, if I have to pick
15:12
all those skills, if I have to pick
15:12
all those skills, if I have to pick these three skills, what do you need?
15:15
these three skills, what do you need?
15:15
these three skills, what do you need? What you will need as a student that
15:18
What you will need as a student that
15:18
What you will need as a student that will help you grow in your career that
15:21
will help you grow in your career that
15:21
will help you grow in your career that will keep you in demand is I would say
15:24
will keep you in demand is I would say
15:24
will keep you in demand is I would say prompt engineering, Vive coding and
15:28
prompt engineering, Vive coding and
15:28
prompt engineering, Vive coding and continuous learning.
15:31
continuous learning.
15:31
continuous learning. Continuous learning is very very
15:33
Continuous learning is very very
15:33
Continuous learning is very very important. These are the three things
15:35
important. These are the three things
15:35
important. These are the three things you can you can take even a screenshot
15:38
you can you can take even a screenshot
15:38
you can you can take even a screenshot of this and write this down. If you
15:40
of this and write this down. If you
15:40
of this and write this down. If you focus on these three things, you'll be
15:42
focus on these three things, you'll be
15:42
focus on these three things, you'll be you'll be set.
15:44
you'll be set.
15:44
you'll be set. You want to learn more about Vive
15:45
You want to learn more about Vive
15:45
You want to learn more about Vive Engineering and this Vive coding and
15:47
Engineering and this Vive coding and
15:47
Engineering and this Vive coding and prompt engineering check out this
15:48
prompt engineering check out this
15:48
prompt engineering check out this website viberondondemand.com
15:52
website viberondondemand.com
15:52
website viberondondemand.com and this is all about Vive coding. You
15:54
and this is all about Vive coding. You
15:54
and this is all about Vive coding. You can literally take a 5hour course on
15:57
can literally take a 5hour course on
15:57
can literally take a 5hour course on Vive coding and you can get going from
15:59
Vive coding and you can get going from
15:59
Vive coding and you can get going from there.
16:06
So this I want to also talk about few
16:09
So this I want to also talk about few
16:09
So this I want to also talk about few things which I learned from you know my
16:11
things which I learned from you know my
16:11
things which I learned from you know my years of experiences. How do you learn
16:14
years of experiences. How do you learn
16:14
years of experiences. How do you learn effectively? And learning is very
16:15
effectively? And learning is very
16:16
effectively? And learning is very important. If you don't learn today,
16:19
important. If you don't learn today,
16:19
important. If you don't learn today, uh you will be obsolete tomorrow. So one
16:22
uh you will be obsolete tomorrow. So one
16:22
uh you will be obsolete tomorrow. So one of the thing I always recommend is talk
16:24
of the thing I always recommend is talk
16:24
of the thing I always recommend is talk about is you have to make learning as a
16:25
about is you have to make learning as a
16:25
about is you have to make learning as a daily habit. It's like exercise. It's
16:28
daily habit. It's like exercise. It's
16:28
daily habit. It's like exercise. It's like you know brushing your teeth. It's
16:31
like you know brushing your teeth. It's
16:32
like you know brushing your teeth. It's like anything else. You have to put
16:34
like anything else. You have to put
16:34
like anything else. You have to put aside some time half an hour. If you
16:37
aside some time half an hour. If you
16:38
aside some time half an hour. If you don't have an hour, an hour is really
16:40
don't have an hour, an hour is really
16:40
don't have an hour, an hour is really good if you can. But if you don't have,
16:42
good if you can. But if you don't have,
16:42
good if you can. But if you don't have, you got to put aside half an hour where
16:45
you got to put aside half an hour where
16:45
you got to put aside half an hour where every day in the morning before you go
16:47
every day in the morning before you go
16:47
every day in the morning before you go to work or you go to school or whenever
16:50
to work or you go to school or whenever
16:50
to work or you go to school or whenever you just
16:52
you just
16:52
you just say, you know what, this is the day I'm
16:54
say, you know what, this is the day I'm
16:54
say, you know what, this is the day I'm going to go somewhere on the website.
16:56
going to go somewhere on the website.
16:56
going to go somewhere on the website. I'm going to learn new things. That's
16:59
I'm going to learn new things. That's
16:59
I'm going to learn new things. That's what you should do. And there's in new
17:01
what you should do. And there's in new
17:01
what you should do. And there's in new technology is everywhere these day. New
17:03
technology is everywhere these day. New
17:03
technology is everywhere these day. New information is everywhere there. You
17:04
information is everywhere there. You
17:04
information is everywhere there. You just have to figure out what platform
17:07
just have to figure out what platform
17:07
just have to figure out what platform you like to choose and just go and learn
17:09
you like to choose and just go and learn
17:09
you like to choose and just go and learn everything. Not only just learn, try to
17:14
everything. Not only just learn, try to
17:14
everything. Not only just learn, try to write about, try to and writing is very
17:18
write about, try to and writing is very
17:18
write about, try to and writing is very important. I always say is that if you
17:21
important. I always say is that if you
17:21
important. I always say is that if you read something is good, you only
17:23
read something is good, you only
17:23
read something is good, you only remember 30%, right? When you read and
17:25
remember 30%, right? When you read and
17:25
remember 30%, right? When you read and write, you almost remember
17:28
write, you almost remember
17:28
write, you almost remember a lot more 50%. And if you read and
17:31
a lot more 50%. And if you read and
17:31
a lot more 50%. And if you read and write and speak, you you remember now
17:33
write and speak, you you remember now
17:33
write and speak, you you remember now 80%. So if you can do those things, that
17:36
80%. So if you can do those things, that
17:36
80%. So if you can do those things, that will be amazing. And you can go and post
17:38
will be amazing. And you can go and post
17:38
will be amazing. And you can go and post this on your social media.
17:41
this on your social media.
17:41
this on your social media. You can do that. So yeah, make a daily
17:44
You can do that. So yeah, make a daily
17:44
You can do that. So yeah, make a daily habit. Then project based learning is
17:48
habit. Then project based learning is
17:48
habit. Then project based learning is important. And you guys already probably
17:50
important. And you guys already probably
17:50
important. And you guys already probably doing it. I know you guys did a
17:52
doing it. I know you guys did a
17:52
doing it. I know you guys did a hackathon. You did amazing job. So
17:55
hackathon. You did amazing job. So
17:55
hackathon. You did amazing job. So learning based on projects. Keep
17:57
learning based on projects. Keep
17:57
learning based on projects. Keep building those projects. The ideas
17:59
building those projects. The ideas
17:59
building those projects. The ideas because that's where you learn more than
18:01
because that's where you learn more than
18:01
because that's where you learn more than anything else.
18:03
anything else.
18:03
anything else. um
18:05
um
18:05
um try to get involved in open source and
18:07
try to get involved in open source and
18:07
try to get involved in open source and community contributions because what is
18:10
community contributions because what is
18:10
community contributions because what is there's another trend change changing
18:12
there's another trend change changing
18:12
there's another trend change changing now in the world is that when
18:17
now in the world is that when
18:17
now in the world is that when recently when back in the day when
18:19
recently when back in the day when
18:19
recently when back in the day when company would hire they'll say oh we are
18:21
company would hire they'll say oh we are
18:21
company would hire they'll say oh we are hiring for full stack developer they
18:24
hiring for full stack developer they
18:24
hiring for full stack developer they will get the rums right they'll get the
18:26
will get the rums right they'll get the
18:26
will get the rums right they'll get the rumés they go through the rumés short
18:28
rumés they go through the rumés short
18:28
rumés they go through the rumés short sort list the rum candidate and
18:30
sort list the rum candidate and
18:30
sort list the rum candidate and interview them that's how used to be but
18:33
interview them that's how used to be but
18:33
interview them that's how used to be but now what start happening is if they're
18:36
now what start happening is if they're
18:36
now what start happening is if they're hiring right now they'll say oh send me
18:38
hiring right now they'll say oh send me
18:38
hiring right now they'll say oh send me your GitHub profile send me your public
18:40
your GitHub profile send me your public
18:40
your GitHub profile send me your public profile so they are now you know want to
18:44
profile so they are now you know want to
18:44
profile so they are now you know want to know that who you are as a person not
18:47
know that who you are as a person not
18:47
know that who you are as a person not just uh how good you are in coding right
18:50
just uh how good you are in coding right
18:50
just uh how good you are in coding right they want to know more than that have
18:52
they want to know more than that have
18:52
they want to know more than that have you done any contributions what kind of
18:54
you done any contributions what kind of
18:54
you done any contributions what kind of contributions have you done there
18:57
contributions have you done there
18:57
contributions have you done there and then last couple of things is
18:59
and then last couple of things is
18:59
and then last couple of things is certification try to get as many as
19:01
certification try to get as many as
19:01
certification try to get as many as certif ifications possible that's always
19:03
certif ifications possible that's always
19:03
certif ifications possible that's always good that's a proof of a skill that you
19:05
good that's a proof of a skill that you
19:06
good that's a proof of a skill that you have actually done something here's the
19:07
have actually done something here's the
19:07
have actually done something here's the proof and then attending more boot camps
19:11
proof and then attending more boot camps
19:11
proof and then attending more boot camps and hackathons I know it's a lot but you
19:15
and hackathons I know it's a lot but you
19:15
and hackathons I know it's a lot but you got to do a little bit of those you for
19:16
got to do a little bit of those you for
19:16
got to do a little bit of those you for example you may do you know one one boot
19:19
example you may do you know one one boot
19:19
example you may do you know one one boot camp every 3 months every four months
19:21
camp every 3 months every four months
19:21
camp every 3 months every four months whenever you get a chance so these are
19:24
whenever you get a chance so these are
19:24
whenever you get a chance so these are the some of the things these days class
19:27
the some of the things these days class
19:27
the some of the things these days class is great books are great but this is
19:30
is great books are great but this is
19:30
is great books are great but this is more important than these is like
19:31
more important than these is like
19:31
more important than these is like hands-on is more important these days
19:34
hands-on is more important these days
19:34
hands-on is more important these days and knowing more things than what's in
19:37
and knowing more things than what's in
19:37
and knowing more things than what's in the book is also very important and how
19:40
the book is also very important and how
19:40
the book is also very important and how do you do that you make it daily habit
19:47
building your digital footprint is very
19:49
building your digital footprint is very
19:49
building your digital footprint is very important these days it's like
19:52
important these days it's like
19:52
important these days it's like since from college when you start
19:54
since from college when you start
19:54
since from college when you start studying in college you're in first year
19:57
studying in college you're in first year
19:57
studying in college you're in first year second year third year doesn't matter
19:59
second year third year doesn't matter
19:59
second year third year doesn't matter you got to start building your footprint
20:00
you got to start building your footprint
20:00
you got to start building your footprint right now because that is a proof that
20:04
right now because that is a proof that
20:04
right now because that is a proof that when you start doing this computer
20:06
when you start doing this computer
20:06
when you start doing this computer programming, computer science learning,
20:08
programming, computer science learning,
20:08
programming, computer science learning, these are the things you have done since
20:10
these are the things you have done since
20:10
these are the things you have done since then. Okay. So there are
20:14
then. Okay. So there are
20:14
then. Okay. So there are websites where you can join here. For
20:16
websites where you can join here. For
20:16
websites where you can join here. For example, this is C# corner. I highly
20:18
example, this is C# corner. I highly
20:18
example, this is C# corner. I highly recommend looks like more than 300 I
20:21
recommend looks like more than 300 I
20:21
recommend looks like more than 300 I think 316
20:23
think 316
20:23
think 316 of you have already joined Corner.
20:26
of you have already joined Corner.
20:26
of you have already joined Corner. Don't just join it. You have to
20:29
Don't just join it. You have to
20:29
Don't just join it. You have to understand what C# corner is. Even
20:31
understand what C# corner is. Even
20:31
understand what C# corner is. Even though name may be C# corner but it's
20:33
though name may be C# corner but it's
20:33
though name may be C# corner but it's really a platform for anybody who's in
20:35
really a platform for anybody who's in
20:35
really a platform for anybody who's in software development. So you need to go
20:37
software development. So you need to go
20:37
software development. So you need to go and create your profile there. Update
20:39
and create your profile there. Update
20:39
and create your profile there. Update your profile what you do. Okay? Put your
20:42
your profile what you do. Okay? Put your
20:42
your profile what you do. Okay? Put your contributions there. Share what you're
20:44
contributions there. Share what you're
20:44
contributions there. Share what you're learning because when you do that this
20:47
learning because when you do that this
20:47
learning because when you do that this all start going on your public profile
20:49
all start going on your public profile
20:49
all start going on your public profile and in future somebody's going to search
20:52
and in future somebody's going to search
20:52
and in future somebody's going to search your name. They're going to look at you.
20:54
your name. They're going to look at you.
20:54
your name. They're going to look at you. They're going to ask Chad GPT who is
20:56
They're going to ask Chad GPT who is
20:56
They're going to ask Chad GPT who is this person. Chat GP is going to get all
20:58
this person. Chat GP is going to get all
20:58
this person. Chat GP is going to get all this information from GitHub, LinkedIn,
21:01
this information from GitHub, LinkedIn,
21:01
this information from GitHub, LinkedIn, Corner and they'll come to your profile.
21:03
Corner and they'll come to your profile.
21:03
Corner and they'll come to your profile. Look at this. So
21:07
Look at this. So
21:07
Look at this. So also create a you know professional
21:09
also create a you know professional
21:09
also create a you know professional profile on LinkedIn. Yes, that's good.
21:11
profile on LinkedIn. Yes, that's good.
21:11
profile on LinkedIn. Yes, that's good. C# corner is good. Blogging once you
21:13
C# corner is good. Blogging once you
21:13
C# corner is good. Blogging once you learn something let's say you every day
21:15
learn something let's say you every day
21:15
learn something let's say you every day now you're learning try to write about
21:18
now you're learning try to write about
21:18
now you're learning try to write about it as I said and blog it. You can blog
21:21
it as I said and blog it. You can blog
21:21
it as I said and blog it. You can blog on LinkedIn on your personal social
21:22
on LinkedIn on your personal social
21:22
on LinkedIn on your personal social media that's great too. But if you blog
21:24
media that's great too. But if you blog
21:24
media that's great too. But if you blog on C# porner now you're getting hundreds
21:27
on C# porner now you're getting hundreds
21:27
on C# porner now you're getting hundreds of people reading that and commenting on
21:29
of people reading that and commenting on
21:29
of people reading that and commenting on that. So that's you're building even
21:31
that. So that's you're building even
21:31
that. So that's you're building even your more it's a digital reputation
21:34
your more it's a digital reputation
21:34
your more it's a digital reputation right you're building a digital social
21:35
right you're building a digital social
21:36
right you're building a digital social reputation
21:39
and there are few things as you can do
21:40
and there are few things as you can do
21:40
and there are few things as you can do if you can really do is speak about it
21:43
if you can really do is speak about it
21:43
if you can really do is speak about it you go and live webinar
21:46
you go and live webinar
21:46
you go and live webinar either you can do your own you can do
21:47
either you can do your own you can do
21:47
either you can do your own you can do YouTube you can see sharp corner has
21:49
YouTube you can see sharp corner has
21:49
YouTube you can see sharp corner has sharp TV like we are doing through this
21:51
sharp TV like we are doing through this
21:51
sharp TV like we are doing through this channel right now we do webinars
21:54
channel right now we do webinars
21:54
channel right now we do webinars whatever there is wherever you find it
21:56
whatever there is wherever you find it
21:56
whatever there is wherever you find it if you can talk about it that's like
21:58
if you can talk about it that's like
21:58
if you can talk about it that's like also building your reputation ation
22:02
also building your reputation ation
22:02
also building your reputation ation and then in the end you build and grow
22:04
and then in the end you build and grow
22:04
and then in the end you build and grow your network. Network how do you grow
22:05
your network. Network how do you grow
22:05
your network. Network how do you grow that? You go meet people, you go online,
22:08
that? You go meet people, you go online,
22:08
that? You go meet people, you go online, connect with people, attend events. So
22:11
connect with people, attend events. So
22:11
connect with people, attend events. So these are the some of the things you can
22:12
these are the some of the things you can
22:12
these are the some of the things you can do
22:14
do
22:14
do um that will help you in coming time in
22:16
um that will help you in coming time in
22:16
um that will help you in coming time in future.
22:21
So what employers look for when
22:22
So what employers look for when
22:22
So what employers look for when companies are hiring? what do they look
22:24
companies are hiring? what do they look
22:24
companies are hiring? what do they look for now in this uh these are the some of
22:26
for now in this uh these are the some of
22:26
for now in this uh these are the some of the skills they look for as I said
22:28
the skills they look for as I said
22:28
the skills they look for as I said besides coding like if if I'm hiring a
22:32
besides coding like if if I'm hiring a
22:32
besides coding like if if I'm hiring a Python developer obviously I expect
22:34
Python developer obviously I expect
22:34
Python developer obviously I expect Python they know Python if I'm hiring a
22:38
Python they know Python if I'm hiring a
22:38
Python they know Python if I'm hiring a fullstack front-end developer fullstack
22:41
fullstack front-end developer fullstack
22:41
fullstack front-end developer fullstack developer with React so I expect them to
22:43
developer with React so I expect them to
22:43
developer with React so I expect them to know React that's great but besides that
22:46
know React that's great but besides that
22:46
know React that's great but besides that what else I'm looking for these are the
22:48
what else I'm looking for these are the
22:48
what else I'm looking for these are the things I'm looking for problem solving
22:50
things I'm looking for problem solving
22:50
things I'm looking for problem solving skills you have problem solving skills
22:53
skills you have problem solving skills
22:53
skills you have problem solving skills or not. And how do you do that? You
22:55
or not. And how do you do that? You
22:55
or not. And how do you do that? You practice, you solve problems.
22:59
practice, you solve problems.
22:59
practice, you solve problems. What are your real world projects and
23:00
What are your real world projects and
23:00
What are your real world projects and contributions like on the platform like
23:03
contributions like on the platform like
23:03
contributions like on the platform like C# Corner, LinkedIn, GitHub, are you
23:06
C# Corner, LinkedIn, GitHub, are you
23:06
C# Corner, LinkedIn, GitHub, are you saying, posting something uh opensource
23:10
saying, posting something uh opensource
23:10
saying, posting something uh opensource other thing is look for a communication.
23:12
other thing is look for a communication.
23:12
other thing is look for a communication. So communication and learning attitude
23:14
So communication and learning attitude
23:14
So communication and learning attitude is very important these days, right?
23:16
is very important these days, right?
23:16
is very important these days, right? Back in the day five years ago if you
23:20
Back in the day five years ago if you
23:20
Back in the day five years ago if you didn't have a learning attitude and your
23:21
didn't have a learning attitude and your
23:21
didn't have a learning attitude and your communication was okay but you're really
23:23
communication was okay but you're really
23:23
communication was okay but you're really amazing coder you were in demand but now
23:27
amazing coder you were in demand but now
23:27
amazing coder you were in demand but now things have changed with AI a lot so as
23:32
things have changed with AI a lot so as
23:32
things have changed with AI a lot so as I said continuous learning now employers
23:34
I said continuous learning now employers
23:34
I said continuous learning now employers look for is that do you learn yourself
23:37
look for is that do you learn yourself
23:37
look for is that do you learn yourself do you upgrade yourself
23:41
other few things is are you involved in
23:43
other few things is are you involved in
23:43
other few things is are you involved in community what are you doing are you
23:45
community what are you doing are you
23:45
community what are you doing are you sharing that trend is also is growing
23:47
sharing that trend is also is growing
23:47
sharing that trend is also is growing big time like are you not just somebody
23:49
big time like are you not just somebody
23:49
big time like are you not just somebody who's sitting in a at your desk and you
23:51
who's sitting in a at your desk and you
23:51
who's sitting in a at your desk and you know do whatever you do are you really
23:55
know do whatever you do are you really
23:55
know do whatever you do are you really out there speaking involving helping all
23:58
out there speaking involving helping all
23:58
out there speaking involving helping all those things
24:00
those things
24:00
those things and then public reputation interest. So
24:02
and then public reputation interest. So
24:02
and then public reputation interest. So again this all builds up like everything
24:04
again this all builds up like everything
24:04
again this all builds up like everything you do start from learning, sharing,
24:08
you do start from learning, sharing,
24:08
you do start from learning, sharing, speaking, writing
24:11
speaking, writing
24:11
speaking, writing um all this all combines together. It
24:14
um all this all combines together. It
24:14
um all this all combines together. It also creates a good profile not only as
24:17
also creates a good profile not only as
24:17
also creates a good profile not only as as well as personality as well.
24:22
Okay, hopefully you guys learning
24:23
Okay, hopefully you guys learning
24:23
Okay, hopefully you guys learning something today.
24:26
something today.
24:26
something today. So if you look out this like let's put
24:29
So if you look out this like let's put
24:29
So if you look out this like let's put this in a carrier road map. If you build
24:31
this in a carrier road map. If you build
24:31
this in a carrier road map. If you build a carrier growth road map, how do you
24:32
a carrier growth road map, how do you
24:32
a carrier growth road map, how do you grow is build a strong network. How do
24:35
grow is build a strong network. How do
24:35
grow is build a strong network. How do you do that? You can start going online
24:37
you do that? You can start going online
24:37
you do that? You can start going online and start publishing things. Go on
24:39
and start publishing things. Go on
24:39
and start publishing things. Go on social media. Have have to have a
24:42
social media. Have have to have a
24:42
social media. Have have to have a continuous learning mindset.
24:44
continuous learning mindset.
24:44
continuous learning mindset. Try to get certifications, solve
24:47
Try to get certifications, solve
24:47
Try to get certifications, solve challenges, participate in hackathons,
24:51
challenges, participate in hackathons,
24:51
challenges, participate in hackathons, attend webinar and conferences and
24:53
attend webinar and conferences and
24:53
attend webinar and conferences and speak. This is the road map you got to
24:57
speak. This is the road map you got to
24:57
speak. This is the road map you got to think about.
24:59
think about.
24:59
think about. Speaking is also very important in
25:00
Speaking is also very important in
25:00
Speaking is also very important in coming time. speaking is going to also
25:02
coming time. speaking is going to also
25:02
coming time. speaking is going to also be important because companies are more
25:05
be important because companies are more
25:05
be important because companies are more now looking for leaders. Companies are
25:08
now looking for leaders. Companies are
25:08
now looking for leaders. Companies are looking for who can come up with the
25:11
looking for who can come up with the
25:11
looking for who can come up with the ideas. So when you speak and talk and
25:13
ideas. So when you speak and talk and
25:13
ideas. So when you speak and talk and I'm listening and watching it's it's
25:16
I'm listening and watching it's it's
25:16
I'm listening and watching it's it's gives me a different perspective
25:18
gives me a different perspective
25:18
gives me a different perspective right. So that's kind of coding is great
25:22
right. So that's kind of coding is great
25:22
right. So that's kind of coding is great what you're doing building is also great
25:25
what you're doing building is also great
25:25
what you're doing building is also great but these days now in coming time when
25:28
but these days now in coming time when
25:28
but these days now in coming time when AI is writing most of the code AI will
25:31
AI is writing most of the code AI will
25:31
AI is writing most of the code AI will write lot of code
25:33
write lot of code
25:33
write lot of code no there's no question in that so how do
25:37
no there's no question in that so how do
25:37
no there's no question in that so how do you separate yourself you separate
25:39
you separate yourself you separate
25:39
you separate yourself you separate yourself by doing these things
25:43
yourself by doing these things
25:43
yourself by doing these things Raman Saga welcome to show good morning
25:46
Raman Saga welcome to show good morning
25:46
Raman Saga welcome to show good morning everybody
25:47
everybody
25:47
everybody so this is how you put these priorities
25:50
so this is how you put these priorities
25:50
so this is how you put these priorities right you want to say you know I want to
25:52
right you want to say you know I want to
25:52
right you want to say you know I want to separate myself you got to start
25:54
separate myself you got to start
25:54
separate myself you got to start thinking on these different topics
26:00
so look at C# corner this is a we are
26:03
so look at C# corner this is a we are
26:03
so look at C# corner this is a we are rebuild we have rebuilt C# corner and it
26:05
rebuild we have rebuilt C# corner and it
26:05
rebuild we have rebuilt C# corner and it is for you guys it is for students this
26:08
is for you guys it is for students this
26:08
is for you guys it is for students this is for young developers who are in
26:12
is for young developers who are in
26:12
is for young developers who are in software industry
26:14
software industry
26:14
software industry and that's what we are building this
26:16
and that's what we are building this
26:16
and that's what we are building this website is for you purpose is you know
26:19
website is for you purpose is you know
26:19
website is for you purpose is you know I'm in LinkedIn a lot I've been LinkedIn
26:21
I'm in LinkedIn a lot I've been LinkedIn
26:21
I'm in LinkedIn a lot I've been LinkedIn for my whole life it's becoming a jungle
26:24
for my whole life it's becoming a jungle
26:24
for my whole life it's becoming a jungle so much spam coming out garbage coming
26:27
so much spam coming out garbage coming
26:27
so much spam coming out garbage coming out so our goal is car owner we are
26:30
out so our goal is car owner we are
26:30
out so our goal is car owner we are building as a community and platform
26:33
building as a community and platform
26:33
building as a community and platform professional platform for learning and
26:35
professional platform for learning and
26:35
professional platform for learning and growth of members so this is where you
26:39
growth of members so this is where you
26:39
growth of members so this is where you can go every day you can go to C# corner
26:41
can go every day you can go to C# corner
26:41
can go every day you can go to C# corner you can see there's new technologies
26:43
you can see there's new technologies
26:43
you can see there's new technologies being published every day there's
26:45
being published every day there's
26:45
being published every day there's articles there are news there even you
26:47
articles there are news there even you
26:47
articles there are news there even you Go and read news every day. You will
26:49
Go and read news every day. You will
26:49
Go and read news every day. You will learn what's being launched in this
26:51
learn what's being launched in this
26:51
learn what's being launched in this industry.
26:53
industry.
26:53
industry. You can also share your knowledge. You
26:55
You can also share your knowledge. You
26:55
You can also share your knowledge. You can if you learn something new, you want
26:57
can if you learn something new, you want
26:57
can if you learn something new, you want to publish article, you want to share
26:59
to publish article, you want to share
26:59
to publish article, you want to share your code, you can do that there. Try to
27:02
your code, you can do that there. Try to
27:02
your code, you can do that there. Try to build your profile. You can also connect
27:05
build your profile. You can also connect
27:05
build your profile. You can also connect with other professionals there. And now
27:07
with other professionals there. And now
27:08
with other professionals there. And now we have I think some of you guys may
27:10
we have I think some of you guys may
27:10
we have I think some of you guys may already know we have these skills badges
27:12
already know we have these skills badges
27:12
already know we have these skills badges and certifications. We are making them
27:15
and certifications. We are making them
27:15
and certifications. We are making them better now. skills batches certification
27:17
better now. skills batches certification
27:17
better now. skills batches certification we are upgrading almost every week. So
27:20
we are upgrading almost every week. So
27:20
we are upgrading almost every week. So when you say you know what I want to
27:21
when you say you know what I want to
27:21
when you say you know what I want to take my challenge and I want to get
27:23
take my challenge and I want to get
27:24
take my challenge and I want to get certified try to go C# mess around there
27:26
certified try to go C# mess around there
27:26
certified try to go C# mess around there if you'd like dislike something give us
27:28
if you'd like dislike something give us
27:28
if you'd like dislike something give us feedback um get more involved in these
27:31
feedback um get more involved in these
27:31
feedback um get more involved in these communities and then end of day or by
27:34
communities and then end of day or by
27:34
communities and then end of day or by doing all that you're actually earning
27:36
doing all that you're actually earning
27:36
doing all that you're actually earning reputation in rewards and rewards is
27:39
reputation in rewards and rewards is
27:39
reputation in rewards and rewards is very important I don't know how many of
27:41
very important I don't know how many of
27:41
very important I don't know how many of you already know sharp rewards how many
27:43
you already know sharp rewards how many
27:43
you already know sharp rewards how many of you have downloaded sharp rewards app
27:46
of you have downloaded sharp rewards app
27:46
of you have downloaded sharp rewards app but now the future is
27:50
but now the future is
27:50
but now the future is where the future is going is that
27:53
where the future is going is that
27:53
where the future is going is that if you are involved in a community like
27:55
if you are involved in a community like
27:55
if you are involved in a community like Corner,
27:57
Corner,
27:57
Corner, you are going to start earning some
27:59
you are going to start earning some
27:59
you are going to start earning some rewards for contributing in the
28:01
rewards for contributing in the
28:01
rewards for contributing in the community. You don't have to do anything
28:02
community. You don't have to do anything
28:02
community. You don't have to do anything extra by just sharing your articles, by
28:06
extra by just sharing your articles, by
28:06
extra by just sharing your articles, by writing articles, blogs, by sharing your
28:09
writing articles, blogs, by sharing your
28:09
writing articles, blogs, by sharing your code or by speaking which is already
28:12
code or by speaking which is already
28:12
code or by speaking which is already helping you grow your career and become
28:15
helping you grow your career and become
28:15
helping you grow your career and become better professional, earn more
28:17
better professional, earn more
28:17
better professional, earn more reputation. You are now also going to
28:20
reputation. You are now also going to
28:20
reputation. You are now also going to start earning these these sharp rewards.
28:24
start earning these these sharp rewards.
28:24
start earning these these sharp rewards. And what are sharp rewards? It's
28:26
And what are sharp rewards? It's
28:26
And what are sharp rewards? It's actually
28:28
actually
28:28
actually a real cryptocurrency called sharp
28:30
a real cryptocurrency called sharp
28:30
a real cryptocurrency called sharp token.
28:32
token.
28:32
token. You start earning this token. We call it
28:34
You start earning this token. We call it
28:34
You start earning this token. We call it learn to earn. More you learn, more you
28:37
learn to earn. More you learn, more you
28:37
learn to earn. More you learn, more you earn. And why are we doing that? You may
28:39
earn. And why are we doing that? You may
28:39
earn. And why are we doing that? You may wonder why are we doing that? Because
28:44
wonder why are we doing that? Because
28:44
wonder why are we doing that? Because learning has been very boring, right?
28:46
learning has been very boring, right?
28:46
learning has been very boring, right? Nobody wants to learn new things. And
28:48
Nobody wants to learn new things. And
28:48
Nobody wants to learn new things. And learning is not fun. Learning is not fun
28:50
learning is not fun. Learning is not fun
28:50
learning is not fun. Learning is not fun like playing cricket. Learning is not
28:52
like playing cricket. Learning is not
28:52
like playing cricket. Learning is not fun as watching movies. So what we're
28:55
fun as watching movies. So what we're
28:55
fun as watching movies. So what we're trying to do is we are gifying learning.
28:59
trying to do is we are gifying learning.
28:59
trying to do is we are gifying learning. We are making learning fun. So you go
29:03
We are making learning fun. So you go
29:03
We are making learning fun. So you go start learning. We are now building this
29:06
start learning. We are now building this
29:06
start learning. We are now building this learning quest. You can now start
29:09
learning quest. You can now start
29:09
learning quest. You can now start learning with your friends and challenge
29:11
learning with your friends and challenge
29:11
learning with your friends and challenge themselves. And there is a every step
29:14
themselves. And there is a every step
29:14
themselves. And there is a every step you achieve something. There's a badge
29:16
you achieve something. There's a badge
29:16
you achieve something. There's a badge and there's tokens awarded to you. And
29:20
and there's tokens awarded to you. And
29:20
and there's tokens awarded to you. And you grow more, you earn more. And once
29:22
you grow more, you earn more. And once
29:22
you grow more, you earn more. And once you earn these tokens now you can take
29:24
you earn these tokens now you can take
29:24
you earn these tokens now you can take these tokens you can spend on some
29:27
these tokens you can spend on some
29:28
these tokens you can spend on some things like what you can spend on career
29:31
things like what you can spend on career
29:31
things like what you can spend on career growth you can spend on hiring a
29:34
growth you can spend on hiring a
29:34
growth you can spend on hiring a freelancer you can spend on getting
29:37
freelancer you can spend on getting
29:37
freelancer you can spend on getting advice you can buy books you can uh do
29:40
advice you can buy books you can uh do
29:40
advice you can buy books you can uh do many other things through these tokens
29:43
many other things through these tokens
29:43
many other things through these tokens in coming time when government
29:45
in coming time when government
29:45
in coming time when government regulations are clear in the in India
29:48
regulations are clear in the in India
29:48
regulations are clear in the in India these tokens you can now take out of
29:51
these tokens you can now take out of
29:51
these tokens you can now take out of this car corner platform and sell it on
29:54
this car corner platform and sell it on
29:54
this car corner platform and sell it on exchanges. You if you this is a real
29:56
exchanges. You if you this is a real
29:56
exchanges. You if you this is a real cryptocurrency
29:58
cryptocurrency
29:58
cryptocurrency like anything else. So right now you
30:01
like anything else. So right now you
30:01
like anything else. So right now you know you may start earning now slowly
30:04
know you may start earning now slowly
30:04
know you may start earning now slowly and over the year you may have billions
30:06
and over the year you may have billions
30:06
and over the year you may have billions of these tokens now you can once Indian
30:09
of these tokens now you can once Indian
30:09
of these tokens now you can once Indian government regulates you can now then go
30:12
government regulates you can now then go
30:12
government regulates you can now then go and sell it and make money out of it.
30:14
and sell it and make money out of it.
30:14
and sell it and make money out of it. That's also coming soon. So we are
30:17
That's also coming soon. So we are
30:17
That's also coming soon. So we are moving ahead with we are building
30:19
moving ahead with we are building
30:19
moving ahead with we are building something that nobody has done before
30:21
something that nobody has done before
30:21
something that nobody has done before which is a learning and growth platform
30:25
which is a learning and growth platform
30:25
which is a learning and growth platform that reward you for learning. That's
30:28
that reward you for learning. That's
30:28
that reward you for learning. That's what we're building on C# for corn for
30:29
what we're building on C# for corn for
30:29
what we're building on C# for corn for so I really want you to go check it out
30:32
so I really want you to go check it out
30:32
so I really want you to go check it out and also there's a app called Sharp
30:34
and also there's a app called Sharp
30:34
and also there's a app called Sharp Rewards app. Sharp rewards app is a it's
30:38
Rewards app. Sharp rewards app is a it's
30:38
Rewards app. Sharp rewards app is a it's both Apple Apple and Google Play. You go
30:41
both Apple Apple and Google Play. You go
30:41
both Apple Apple and Google Play. You go to Google Play, download the app and it
30:44
to Google Play, download the app and it
30:44
to Google Play, download the app and it has activities to do in this. You can do
30:47
has activities to do in this. You can do
30:47
has activities to do in this. You can do few activities. There are quizzes. We
30:50
few activities. There are quizzes. We
30:50
few activities. There are quizzes. We are bringing more challenges in there.
30:52
are bringing more challenges in there.
30:52
are bringing more challenges in there. We are going to bring uh GK in there. We
30:55
We are going to bring uh GK in there. We
30:55
We are going to bring uh GK in there. We are going to bring quest there. So, it's
30:57
are going to bring quest there. So, it's
30:57
are going to bring quest there. So, it's going to bring more a lot more learning
31:00
going to bring more a lot more learning
31:00
going to bring more a lot more learning and every time you learn you actually
31:01
and every time you learn you actually
31:01
and every time you learn you actually earning these tokens.
31:04
earning these tokens.
31:04
earning these tokens. Now everything you do in the community
31:07
Now everything you do in the community
31:07
Now everything you do in the community it also going on your profile and that's
31:10
it also going on your profile and that's
31:10
it also going on your profile and that's the most important part is that um it's
31:14
the most important part is that um it's
31:14
the most important part is that um it's going on your profile. For example, if
31:17
going on your profile. For example, if
31:17
going on your profile. For example, if you take a certification or you learn
31:19
you take a certification or you learn
31:19
you take a certification or you learn something or you took a challenge, we
31:22
something or you took a challenge, we
31:22
something or you took a challenge, we are now putting that on blockchain.
31:25
are now putting that on blockchain.
31:25
are now putting that on blockchain. Now there's a proof that this person
31:27
Now there's a proof that this person
31:27
Now there's a proof that this person learned this skill on that day.
31:31
learned this skill on that day.
31:31
learned this skill on that day. So imagine in 3 years or five years down
31:34
So imagine in 3 years or five years down
31:34
So imagine in 3 years or five years down the road somebody's going to interview
31:37
the road somebody's going to interview
31:37
the road somebody's going to interview and look at your profile and they can
31:38
and look at your profile and they can
31:38
and look at your profile and they can ask and they'll say oh let me see if
31:41
ask and they'll say oh let me see if
31:41
ask and they'll say oh let me see if this guy knows oh oh he's already taken
31:44
this guy knows oh oh he's already taken
31:44
this guy knows oh oh he's already taken this challenge he's took the
31:45
this challenge he's took the
31:45
this challenge he's took the certification on two years earlier and
31:48
certification on two years earlier and
31:48
certification on two years earlier and there's a proof on blog chain so now as
31:51
there's a proof on blog chain so now as
31:51
there's a proof on blog chain so now as an employer I'm already filtering a lot
31:55
an employer I'm already filtering a lot
31:55
an employer I'm already filtering a lot of these candidate based on what they
31:57
of these candidate based on what they
31:57
of these candidate based on what they have done on my profile so I hope I'm
32:00
have done on my profile so I hope I'm
32:00
have done on my profile so I hope I'm making sense This guys have your
32:01
making sense This guys have your
32:01
making sense This guys have your questions ready. I want you to ask
32:04
questions ready. I want you to ask
32:04
questions ready. I want you to ask questions. Make sure the questions do
32:06
questions. Make sure the questions do
32:06
questions. Make sure the questions do you know we answer some of the
32:07
you know we answer some of the
32:07
you know we answer some of the questions. Another thing we have on C#
32:10
questions. Another thing we have on C#
32:10
questions. Another thing we have on C# corner we are launching it. It's really
32:12
corner we are launching it. It's really
32:12
corner we are launching it. It's really new feature called bounties and we are
32:15
new feature called bounties and we are
32:15
new feature called bounties and we are still changing playing with the feature.
32:17
still changing playing with the feature.
32:17
still changing playing with the feature. Uh this is going to come change a lot
32:19
Uh this is going to come change a lot
32:19
Uh this is going to come change a lot but right now we are running a bounty
32:21
but right now we are running a bounty
32:21
but right now we are running a bounty called AI for peace as you can see. So
32:24
called AI for peace as you can see. So
32:24
called AI for peace as you can see. So if you go to C# corner/bounties
32:27
if you go to C# corner/bounties
32:27
if you go to C# corner/bounties um
32:29
um
32:29
um you can go there and there's AI for
32:31
you can go there and there's AI for
32:31
you can go there and there's AI for peace. So there is $3,000 cash prize for
32:33
peace. So there is $3,000 cash prize for
32:33
peace. So there is $3,000 cash prize for that. Five people going to win or I
32:35
that. Five people going to win or I
32:36
that. Five people going to win or I think 10 people are going to win this
32:38
think 10 people are going to win this
32:38
think 10 people are going to win this prize. Uh where you have to submit an
32:41
prize. Uh where you have to submit an
32:41
prize. Uh where you have to submit an idea about how AI can be used for peace.
32:44
idea about how AI can be used for peace.
32:44
idea about how AI can be used for peace. Just an idea. Uh we have partnered with
32:47
Just an idea. Uh we have partnered with
32:48
Just an idea. Uh we have partnered with company it's called defunding. funding.
32:50
company it's called defunding. funding.
32:50
company it's called defunding. funding. It's a company that funds AI projects.
32:54
It's a company that funds AI projects.
32:54
It's a company that funds AI projects. There are more more bounties coming here
32:56
There are more more bounties coming here
32:56
There are more more bounties coming here too. So keep an eye on C# Corner. Keep
32:59
too. So keep an eye on C# Corner. Keep
32:59
too. So keep an eye on C# Corner. Keep visiting it. Get involved because we are
33:01
visiting it. Get involved because we are
33:01
visiting it. Get involved because we are gamifying this whole platform and end
33:05
gamifying this whole platform and end
33:05
gamifying this whole platform and end goal is that when you're learning
33:08
goal is that when you're learning
33:08
goal is that when you're learning something there, you are just having
33:09
something there, you are just having
33:09
something there, you are just having fun. That's the idea.
33:15
What else you can do C# sharp corner for
33:17
What else you can do C# sharp corner for
33:17
What else you can do C# sharp corner for students is that you can get free books
33:19
students is that you can get free books
33:19
students is that you can get free books tutorials. You already know hack India
33:21
tutorials. You already know hack India
33:21
tutorials. You already know hack India we are doing these hack India hackathons
33:24
we are doing these hack India hackathons
33:24
we are doing these hack India hackathons we also have some of these online
33:27
we also have some of these online
33:27
we also have some of these online virtual conferences focused on students
33:30
virtual conferences focused on students
33:30
virtual conferences focused on students there's every week there are different
33:31
there's every week there are different
33:31
there's every week there are different webinar and virtual conferences are
33:33
webinar and virtual conferences are
33:33
webinar and virtual conferences are happening every week at least webinars
33:37
happening every week at least webinars
33:37
happening every week at least webinars there different shows for example prompt
33:39
there different shows for example prompt
33:39
there different shows for example prompt engineering is happening I talk about
33:41
engineering is happening I talk about
33:41
engineering is happening I talk about prompt engineering some Saturdays
33:44
prompt engineering some Saturdays
33:44
prompt engineering some Saturdays um jobs listing is there as well we are
33:46
um jobs listing is there as well we are
33:46
um jobs listing is there as well we are going to launch internships as well and
33:49
going to launch internships as well and
33:49
going to launch internships as well and oh By the way, we also have launched a
33:52
oh By the way, we also have launched a
33:52
oh By the way, we also have launched a job ready internship program. So, some
33:54
job ready internship program. So, some
33:54
job ready internship program. So, some of the students they have they have
33:58
of the students they have they have
33:58
of the students they have they have problems getting internships, right? So,
34:01
problems getting internships, right? So,
34:01
problems getting internships, right? So, we have worked with these companies
34:02
we have worked with these companies
34:02
we have worked with these companies where they
34:04
where they
34:04
where they uh they said to they told us and we have
34:07
uh they said to they told us and we have
34:07
uh they said to they told us and we have partnership with them saying if you can
34:09
partnership with them saying if you can
34:09
partnership with them saying if you can train or provide the internship these
34:11
train or provide the internship these
34:11
train or provide the internship these students from these technology they will
34:13
students from these technology they will
34:13
students from these technology they will hire them or at least we can set up
34:15
hire them or at least we can set up
34:16
hire them or at least we can set up interviews with them. So if you are
34:17
interviews with them. So if you are
34:17
interviews with them. So if you are interested in joining some of those
34:19
interested in joining some of those
34:19
interested in joining some of those training you are having hard time your
34:22
training you are having hard time your
34:22
training you are having hard time your hard time finding these internships you
34:25
hard time finding these internships you
34:25
hard time finding these internships you can reach out to here and ask your you
34:29
can reach out to here and ask your you
34:29
can reach out to here and ask your you know career counselor who is helping you
34:31
know career counselor who is helping you
34:31
know career counselor who is helping you at school they can reach out to and we
34:33
at school they can reach out to and we
34:34
at school they can reach out to and we can get you introduction to this job
34:36
can get you introduction to this job
34:36
can get you introduction to this job readytorship programs.
34:39
readytorship programs.
34:39
readytorship programs. So again there's more things coming on
34:42
So again there's more things coming on
34:42
So again there's more things coming on C# corner prompt engineering a IML
34:46
C# corner prompt engineering a IML
34:46
C# corner prompt engineering a IML uh V coding trainings are starting as
34:48
uh V coding trainings are starting as
34:48
uh V coding trainings are starting as well. So just keep visiting stay up to
34:51
well. So just keep visiting stay up to
34:51
well. So just keep visiting stay up to date. I hope you learned something
34:53
date. I hope you learned something
34:54
date. I hope you learned something today. Let's take some questions because
34:55
today. Let's take some questions because
34:55
today. Let's take some questions because I like to take questions and answer your
34:58
I like to take questions and answer your
34:58
I like to take questions and answer your questions.
35:06
That's a great question. When did the
35:08
That's a great question. When did the
35:08
That's a great question. When did the results when announced for AI for peace?
35:10
results when announced for AI for peace?
35:10
results when announced for AI for peace? That's a good question. Um, we were
35:13
That's a good question. Um, we were
35:13
That's a good question. Um, we were hoping that we will get thousand
35:15
hoping that we will get thousand
35:15
hoping that we will get thousand ideas. That's when we were thinking to
35:17
ideas. That's when we were thinking to
35:18
ideas. That's when we were thinking to announce I think right now we have about
35:20
announce I think right now we have about
35:20
announce I think right now we have about 500 ideas. So we still have halfway to
35:23
500 ideas. So we still have halfway to
35:23
500 ideas. So we still have halfway to go. We are waiting on more ideas to
35:26
go. We are waiting on more ideas to
35:26
go. We are waiting on more ideas to come. The defunding is expecting
35:29
come. The defunding is expecting
35:29
come. The defunding is expecting thousand ideas. Once we have thousand,
35:31
thousand ideas. Once we have thousand,
35:31
thousand ideas. Once we have thousand, we will submit and announce it for that.
35:38
Okay, any more questions? Let's see. How
35:41
Okay, any more questions? Let's see. How
35:41
Okay, any more questions? Let's see. How about questions from students? Did you
35:43
about questions from students? Did you
35:43
about questions from students? Did you guys enjoy it? Did you learn something
35:46
guys enjoy it? Did you learn something
35:46
guys enjoy it? Did you learn something new today?
36:03
You can also jump in. If uh there are no
36:05
You can also jump in. If uh there are no
36:05
You can also jump in. If uh there are no questions, then we can be done. There
36:08
questions, then we can be done. There
36:08
questions, then we can be done. There are questions. Let's ask uh post them
36:10
are questions. Let's ask uh post them
36:10
are questions. Let's ask uh post them here.
36:19
Any road map for become AI engineer from
36:23
Any road map for become AI engineer from
36:23
Any road map for become AI engineer from net developer? Ramas okay that's a great
36:26
net developer? Ramas okay that's a great
36:26
net developer? Ramas okay that's a great question like if you are a net developer
36:28
question like if you are a net developer
36:28
question like if you are a net developer how do you become a engineer so the way
36:31
how do you become a engineer so the way
36:31
how do you become a engineer so the way you have to think is if you want to
36:33
you have to think is if you want to
36:33
you have to think is if you want to become a engineer you have to rethink
36:35
become a engineer you have to rethink
36:35
become a engineer you have to rethink and relearn everything becausen net is
36:38
and relearn everything becausen net is
36:38
and relearn everything becausen net is fine you can do some things with the
36:42
fine you can do some things with the
36:42
fine you can do some things with the you can do some AI withnet but it's it's
36:45
you can do some AI withnet but it's it's
36:45
you can do some AI withnet but it's it's not really pure AI if you learn for
36:49
not really pure AI if you learn for
36:49
not really pure AI if you learn for example Azure has its own AI you can
36:52
example Azure has its own AI you can
36:52
example Azure has its own AI you can build using Azure and C but true AI is
36:56
build using Azure and C but true AI is
36:56
build using Azure and C but true AI is really
36:57
really
36:58
really Python ML libraries
37:01
Python ML libraries
37:01
Python ML libraries and there's this new world of LLMs
37:04
and there's this new world of LLMs
37:04
and there's this new world of LLMs wherenet really doesn't play much role
37:08
wherenet really doesn't play much role
37:08
wherenet really doesn't play much role and if you want to really get into you
37:10
and if you want to really get into you
37:10
and if you want to really get into you don't need to if you just say you know
37:11
don't need to if you just say you know
37:11
don't need to if you just say you know what can I still be getting jobs inn net
37:15
what can I still be getting jobs inn net
37:15
what can I still be getting jobs inn net sure you will definitely have more jobs
37:16
sure you will definitely have more jobs
37:16
sure you will definitely have more jobs inn net the number of jobs will shrink
37:20
inn net the number of jobs will shrink
37:20
inn net the number of jobs will shrink obviously
37:22
obviously
37:22
obviously Um but if you want to become an AI ML
37:27
Um but if you want to become an AI ML
37:27
Um but if you want to become an AI ML engineer, it's basically
37:30
engineer, it's basically
37:30
engineer, it's basically almost like
37:33
almost like
37:33
almost like retraining your mind starting from a
37:35
retraining your mind starting from a
37:35
retraining your mind starting from a scratch.
37:39
So there's another question from Joshua.
37:41
So there's another question from Joshua.
37:41
So there's another question from Joshua. Is there any prerequisites
37:44
Is there any prerequisites
37:44
Is there any prerequisites for the internships for
37:48
for the internships for
37:48
for the internships for second or third year students?
37:53
Um
37:55
Um
37:55
Um internships are different. Uh if you're
37:57
internships are different. Uh if you're
37:57
internships are different. Uh if you're talking about what internship we have,
37:59
talking about what internship we have,
37:59
talking about what internship we have, they are for final year. They are
38:00
they are for final year. They are
38:00
they are for final year. They are internships we have is for final year.
38:04
internships we have is for final year.
38:04
internships we have is for final year. So then you are when your internship is
38:06
So then you are when your internship is
38:06
So then you are when your internship is done, you are being introduced to the
38:08
done, you are being introduced to the
38:08
done, you are being introduced to the companies. So they can interview and get
38:10
companies. So they can interview and get
38:10
companies. So they can interview and get a job if that's the question.
38:14
a job if that's the question.
38:14
a job if that's the question. So that is the only prerequisites and
38:16
So that is the only prerequisites and
38:16
So that is the only prerequisites and obviously there is a qualification.
38:19
obviously there is a qualification.
38:19
obviously there is a qualification. uh we can't just you know give so many
38:22
uh we can't just you know give so many
38:22
uh we can't just you know give so many internships you have to also qualify for
38:25
internships you have to also qualify for
38:25
internships you have to also qualify for that
38:30
all right
38:33
can you tell us about agentic AI that's
38:36
can you tell us about agentic AI that's
38:36
can you tell us about agentic AI that's a great question
38:38
a great question
38:38
a great question agentic AI so there's a new world coming
38:43
agentic AI so there's a new world coming
38:43
agentic AI so there's a new world coming and that's called agentic AI and I
38:45
and that's called agentic AI and I
38:45
and that's called agentic AI and I believe that will take over the world in
38:47
believe that will take over the world in
38:48
believe that will take over the world in coming time
38:49
coming time
38:49
coming time which is already happening.
38:52
which is already happening.
38:52
which is already happening. Agents, AI agents are going to take over
38:55
Agents, AI agents are going to take over
38:55
Agents, AI agents are going to take over the world. In other words,
38:58
the world. In other words,
38:58
the world. In other words, when people are going online, they will
39:01
when people are going online, they will
39:01
when people are going online, they will not be going online. They will not be
39:03
not be going online. They will not be
39:03
not be going online. They will not be visiting a website. Sure, there will be
39:05
visiting a website. Sure, there will be
39:05
visiting a website. Sure, there will be some websites and app, but most of the d
39:09
some websites and app, but most of the d
39:09
some websites and app, but most of the d work will be done by these AI agents
39:11
work will be done by these AI agents
39:11
work will be done by these AI agents they're running at night. For example,
39:14
they're running at night. For example,
39:14
they're running at night. For example, you can create an agents, multiple
39:16
you can create an agents, multiple
39:16
you can create an agents, multiple agents will work together. You can
39:18
agents will work together. You can
39:18
agents will work together. You can schedule some task at night saying, "Oh,
39:22
schedule some task at night saying, "Oh,
39:22
schedule some task at night saying, "Oh, I want you to at night, all night, I
39:24
I want you to at night, all night, I
39:24
I want you to at night, all night, I want you to do these things for me. For
39:25
want you to do these things for me. For
39:26
want you to do these things for me. For example, read my emails, all emails in
39:29
example, read my emails, all emails in
39:29
example, read my emails, all emails in all day. Find the emails that's
39:31
all day. Find the emails that's
39:31
all day. Find the emails that's important for me. Reply those emails,
39:35
important for me. Reply those emails,
39:35
important for me. Reply those emails, send me a summary, all that. You'll
39:37
send me a summary, all that. You'll
39:37
send me a summary, all that. You'll create a workflow that will involve
39:39
create a workflow that will involve
39:40
create a workflow that will involve multiple AI agents.
39:42
multiple AI agents.
39:42
multiple AI agents. and agents will do all the work for you.
39:45
and agents will do all the work for you.
39:45
and agents will do all the work for you. So some experts are also predicting that
39:48
So some experts are also predicting that
39:48
So some experts are also predicting that in coming time everybody will have their
39:50
in coming time everybody will have their
39:50
in coming time everybody will have their own AI doctor, everybody will have their
39:54
own AI doctor, everybody will have their
39:54
own AI doctor, everybody will have their own AI trainer, AI tutor and then it is
39:58
own AI trainer, AI tutor and then it is
39:58
own AI trainer, AI tutor and then it is all are almost like pretty much AI
40:00
all are almost like pretty much AI
40:00
all are almost like pretty much AI agents, right? And they will do and run.
40:04
agents, right? And they will do and run.
40:04
agents, right? And they will do and run. So more you learn about AI, learn about
40:08
So more you learn about AI, learn about
40:08
So more you learn about AI, learn about agentic AI. Agentic AI means
40:13
agentic AI. Agentic AI means
40:13
agentic AI. Agentic AI means how do you build agents, how do you use
40:16
how do you build agents, how do you use
40:16
how do you build agents, how do you use agents? There's so many agents are going
40:18
agents? There's so many agents are going
40:18
agents? There's so many agents are going to be available in coming time. Learning
40:21
to be available in coming time. Learning
40:21
to be available in coming time. Learning how to use them is also going to be a
40:23
how to use them is also going to be a
40:23
how to use them is also going to be a big biggest skill.
40:25
big biggest skill.
40:25
big biggest skill. In coming time there will be less need
40:27
In coming time there will be less need
40:27
In coming time there will be less need of building agent. There'll be more need
40:29
of building agent. There'll be more need
40:29
of building agent. There'll be more need of how to use different agents. For
40:33
of how to use different agents. For
40:33
of how to use different agents. For example, right now if you are a I don't
40:37
example, right now if you are a I don't
40:37
example, right now if you are a I don't know you are an inde you know cloud
40:38
know you are an inde you know cloud
40:38
know you are an inde you know cloud engineer you should know there's so many
40:41
engineer you should know there's so many
40:41
engineer you should know there's so many features and products and services
40:44
features and products and services
40:44
features and products and services available in Azure cloud all you need to
40:46
available in Azure cloud all you need to
40:46
available in Azure cloud all you need to know is how to use them and use them to
40:49
know is how to use them and use them to
40:49
know is how to use them and use them to build a workflow application and so on
40:52
build a workflow application and so on
40:52
build a workflow application and so on so forth so that's what will be the
40:54
so forth so that's what will be the
40:54
so forth so that's what will be the future in coming time there'll be a
40:56
future in coming time there'll be a
40:56
future in coming time there'll be a bunch of AI agents for doing different
40:58
bunch of AI agents for doing different
40:58
bunch of AI agents for doing different tasks you just have to figure out
41:00
tasks you just have to figure out
41:00
tasks you just have to figure out configure them and use them that's what
41:02
configure them and use them that's what
41:02
configure them and use them that's what businesses will need more.
41:04
businesses will need more.
41:04
businesses will need more. Um so yes that's a that's a if you look
41:08
Um so yes that's a that's a if you look
41:08
Um so yes that's a that's a if you look at the advanced AI that will be the
41:11
at the advanced AI that will be the
41:11
at the advanced AI that will be the topic you should be learning.
41:14
topic you should be learning.
41:14
topic you should be learning. Um that is the future. Agentic AI is the
41:17
Um that is the future. Agentic AI is the
41:17
Um that is the future. Agentic AI is the future.
41:23
What are the most promising areas of
41:25
What are the most promising areas of
41:25
What are the most promising areas of research in AI in next five years?
41:27
research in AI in next five years?
41:27
research in AI in next five years? There's a lot of every area is amazing
41:29
There's a lot of every area is amazing
41:30
There's a lot of every area is amazing and I think the the solving some of the
41:33
and I think the the solving some of the
41:33
and I think the the solving some of the health care problems biggest healthcare
41:35
health care problems biggest healthcare
41:36
health care problems biggest healthcare problem is a big innovation. So for
41:38
problem is a big innovation. So for
41:38
problem is a big innovation. So for example cancer research right anything
41:41
example cancer research right anything
41:41
example cancer research right anything what happens is when you there's you
41:43
what happens is when you there's you
41:43
what happens is when you there's you know disease like rare disease or cancer
41:45
know disease like rare disease or cancer
41:45
know disease like rare disease or cancer these happen doctors it take them so
41:48
these happen doctors it take them so
41:48
these happen doctors it take them so much time to analyze and sometimes they
41:50
much time to analyze and sometimes they
41:50
much time to analyze and sometimes they give wrong results in coming time or
41:53
give wrong results in coming time or
41:53
give wrong results in coming time or already happening now there are models
41:55
already happening now there are models
41:55
already happening now there are models LLM large language models where I can
41:58
LLM large language models where I can
41:58
LLM large language models where I can put you know you scan the body and say
42:01
put you know you scan the body and say
42:01
put you know you scan the body and say this is the cancer you put the body in
42:03
this is the cancer you put the body in
42:03
this is the cancer you put the body in AI AI now goes through these millions of
42:07
AI AI now goes through these millions of
42:07
AI AI now goes through these millions of millions of screens and images in pre-
42:09
millions of screens and images in pre-
42:09
millions of screens and images in pre- data they already have and they can
42:12
data they already have and they can
42:12
data they already have and they can diagnose this much better than the
42:14
diagnose this much better than the
42:14
diagnose this much better than the doctors the results are amazing same
42:17
doctors the results are amazing same
42:17
doctors the results are amazing same thing with the with these clinical
42:20
thing with the with these clinical
42:20
thing with the with these clinical trials same thing with the space
42:23
trials same thing with the space
42:23
trials same thing with the space research so a lot of these things we
42:26
research so a lot of these things we
42:26
research so a lot of these things we were unable to do because of human
42:29
were unable to do because of human
42:29
were unable to do because of human didn't have enough time now AI can do
42:32
didn't have enough time now AI can do
42:32
didn't have enough time now AI can do that much faster so almost like even in
42:36
that much faster so almost like even in
42:36
that much faster so almost like even in um anything any area that needed lot of
42:40
um anything any area that needed lot of
42:40
um anything any area that needed lot of work lot of data that was not possible
42:43
work lot of data that was not possible
42:43
work lot of data that was not possible before now you can do that by using AI
42:48
before now you can do that by using AI
42:48
before now you can do that by using AI so AI is going to revolutionize the
42:50
so AI is going to revolutionize the
42:50
so AI is going to revolutionize the whole world things will move much faster
42:52
whole world things will move much faster
42:52
whole world things will move much faster things will get too fast in coming time
42:56
things will get too fast in coming time
42:56
things will get too fast in coming time that even Elon Musk and some of the
42:59
that even Elon Musk and some of the
42:59
that even Elon Musk and some of the experts are saying that it will cut down
43:02
experts are saying that it will cut down
43:02
experts are saying that it will cut down lot of our costs because right now lot
43:05
lot of our costs because right now lot
43:05
lot of our costs because right now lot of cost is because things are slow and
43:07
of cost is because things are slow and
43:07
of cost is because things are slow and there's too many people involved when
43:09
there's too many people involved when
43:09
there's too many people involved when doing doing all this work.
43:13
doing doing all this work.
43:13
doing doing all this work. You know AI and robotics for example
43:14
You know AI and robotics for example
43:14
You know AI and robotics for example you're building cars right AI will do
43:17
you're building cars right AI will do
43:17
you're building cars right AI will do quickly build those cars you don't need
43:19
quickly build those cars you don't need
43:19
quickly build those cars you don't need human labor anymore and they can do
43:21
human labor anymore and they can do
43:21
human labor anymore and they can do things faster. So this is every almost
43:24
things faster. So this is every almost
43:24
things faster. So this is every almost every area is going to be re
43:26
every area is going to be re
43:26
every area is going to be re revolutionized in this
43:28
revolutionized in this
43:28
revolutionized in this using AI.
43:33
[Music]
43:37
Um how to become a prompt engineer? What
43:39
Um how to become a prompt engineer? What
43:39
Um how to become a prompt engineer? What are the qualifications to become a
43:41
are the qualifications to become a
43:41
are the qualifications to become a prompt engineer by damu?
43:44
prompt engineer by damu?
43:44
prompt engineer by damu? um prompt engineering is um
43:49
um prompt engineering is um
43:49
um prompt engineering is um it's a quick I'll give you a quick in
43:51
it's a quick I'll give you a quick in
43:51
it's a quick I'll give you a quick in one minute is that it's
43:55
one minute is that it's
43:55
one minute is that it's there's a AI
43:57
there's a AI
43:57
there's a AI that does the for example you go to chat
44:00
that does the for example you go to chat
44:00
that does the for example you go to chat GPT and ask something hey write me a
44:03
GPT and ask something hey write me a
44:03
GPT and ask something hey write me a code so you can say write me a code AI
44:07
code so you can say write me a code AI
44:07
code so you can say write me a code AI goes chat GPT passes the prompt that
44:11
goes chat GPT passes the prompt that
44:11
goes chat GPT passes the prompt that input is called prompt what you're
44:12
input is called prompt what you're
44:12
input is called prompt what you're saying input is prompt AI takes that
44:16
saying input is prompt AI takes that
44:16
saying input is prompt AI takes that prompt which is actually LLM behind the
44:19
prompt which is actually LLM behind the
44:19
prompt which is actually LLM behind the scene and then it generates output and
44:22
scene and then it generates output and
44:22
scene and then it generates output and then gives you output back. So the
44:24
then gives you output back. So the
44:24
then gives you output back. So the crafting the art of the crafting or
44:26
crafting the art of the crafting or
44:26
crafting the art of the crafting or creating this prompt is called prompt
44:28
creating this prompt is called prompt
44:28
creating this prompt is called prompt engineering. So prompt engineering is
44:29
engineering. So prompt engineering is
44:29
engineering. So prompt engineering is not really engineering to be honest.
44:31
not really engineering to be honest.
44:31
not really engineering to be honest. It's more like a art. It's more like art
44:34
It's more like a art. It's more like art
44:34
It's more like a art. It's more like art and a skill. So how do you craft these
44:37
and a skill. So how do you craft these
44:37
and a skill. So how do you craft these prompts and there are some certain
44:39
prompts and there are some certain
44:40
prompts and there are some certain techniques to that and it's not hard to
44:42
techniques to that and it's not hard to
44:42
techniques to that and it's not hard to become a prompt engineer. Uh this is not
44:45
become a prompt engineer. Uh this is not
44:45
become a prompt engineer. Uh this is not a degree this is not a some kind of you
44:48
a degree this is not a some kind of you
44:48
a degree this is not a some kind of you know um it's a there's actually course
44:52
know um it's a there's actually course
44:52
know um it's a there's actually course for uh we launch a course right now on
44:55
for uh we launch a course right now on
44:55
for uh we launch a course right now on Corner and Viber on demand. It's a
44:58
Corner and Viber on demand. It's a
44:58
Corner and Viber on demand. It's a 10-hour course. You can become a prompt
45:00
10-hour course. You can become a prompt
45:00
10-hour course. You can become a prompt engineer in 10 hours. Go check it out. I
45:04
engineer in 10 hours. Go check it out. I
45:04
engineer in 10 hours. Go check it out. I think this is the school everybody
45:05
think this is the school everybody
45:05
think this is the school everybody should have. The reason you want to
45:08
should have. The reason you want to
45:08
should have. The reason you want to become a prompt engineer is because when
45:11
become a prompt engineer is because when
45:11
become a prompt engineer is because when you talk to AI, AI understands certain
45:14
you talk to AI, AI understands certain
45:14
you talk to AI, AI understands certain ways even though it will figure out but
45:17
ways even though it will figure out but
45:17
ways even though it will figure out but more
45:19
more
45:19
more defined
45:20
defined
45:20
defined exact question and input you give it to
45:23
exact question and input you give it to
45:23
exact question and input you give it to you more faster and cheaper it will
45:27
you more faster and cheaper it will
45:27
you more faster and cheaper it will become for you and for the world. So for
45:29
become for you and for the world. So for
45:29
become for you and for the world. So for example they just found a research that
45:32
example they just found a research that
45:32
example they just found a research that by just saying hi to chat GPT before
45:35
by just saying hi to chat GPT before
45:35
by just saying hi to chat GPT before your sentence you put hi right you say
45:39
your sentence you put hi right you say
45:39
your sentence you put hi right you say hi say hi
45:42
hi say hi
45:42
hi say hi can you create a email for me by saying
45:45
can you create a email for me by saying
45:45
can you create a email for me by saying hi
45:47
hi
45:47
hi open AI it's costing openai millions of
45:50
open AI it's costing openai millions of
45:50
open AI it's costing openai millions of dollars per day because every time you
45:53
dollars per day because every time you
45:54
dollars per day because every time you add extra letter extra word the
45:56
add extra letter extra word the
45:56
add extra letter extra word the processing goes filters out there's a
45:58
processing goes filters out there's a
45:58
processing goes filters out there's a cost involved in that. There's a lot of
46:01
cost involved in that. There's a lot of
46:01
cost involved in that. There's a lot of machines running. So there's art to
46:03
machines running. So there's art to
46:03
machines running. So there's art to that. There's skills to that in prompt
46:05
that. There's skills to that in prompt
46:05
that. There's skills to that in prompt engineering. And um I have a my friend
46:09
engineering. And um I have a my friend
46:09
engineering. And um I have a my friend is who is called trainer John. We are
46:11
is who is called trainer John. We are
46:11
is who is called trainer John. We are training this how to become a certified
46:14
training this how to become a certified
46:14
training this how to become a certified prompt engineer. We have a 10-hour
46:16
prompt engineer. We have a 10-hour
46:16
prompt engineer. We have a 10-hour course for 10 days, 1 hour each day.
46:19
course for 10 days, 1 hour each day.
46:19
course for 10 days, 1 hour each day. Check it out on car.com/trainings
46:23
Check it out on car.com/trainings
46:23
Check it out on car.com/trainings or also on Viber ondemand.
46:33
How do I find which domain passionate
46:35
How do I find which domain passionate
46:35
How do I find which domain passionate about the recommended platform to grow
46:38
about the recommended platform to grow
46:38
about the recommended platform to grow out grow our skill? How do I find which
46:40
out grow our skill? How do I find which
46:40
out grow our skill? How do I find which domain passionate about
46:44
domain passionate about
46:44
domain passionate about and recommended platform? So how do you
46:45
and recommended platform? So how do you
46:46
and recommended platform? So how do you find out what you are passionate about?
46:49
find out what you are passionate about?
46:49
find out what you are passionate about? Uh
46:50
Uh
46:50
Uh that's a great question. It's really
46:52
that's a great question. It's really
46:52
that's a great question. It's really hard sometimes. Um
46:55
hard sometimes. Um
46:55
hard sometimes. Um the way you need to think is when you
46:57
the way you need to think is when you
46:57
the way you need to think is when you have lot of time, let's say you're
46:59
have lot of time, let's say you're
46:59
have lot of time, let's say you're sitting at home one day, you have
47:01
sitting at home one day, you have
47:01
sitting at home one day, you have nothing else to do.
47:04
nothing else to do.
47:04
nothing else to do. What is that you end up doing? And I'm
47:06
What is that you end up doing? And I'm
47:06
What is that you end up doing? And I'm not talking about going through social
47:07
not talking about going through social
47:07
not talking about going through social media. I'm not talking about watching
47:09
media. I'm not talking about watching
47:09
media. I'm not talking about watching movie. What is that you like to do when
47:13
movie. What is that you like to do when
47:13
movie. What is that you like to do when you're sitting and doing nothing?
47:16
you're sitting and doing nothing?
47:16
you're sitting and doing nothing? Like do you like gardening or do you
47:18
Like do you like gardening or do you
47:18
Like do you like gardening or do you like singing? I don't know whatever that
47:21
like singing? I don't know whatever that
47:21
like singing? I don't know whatever that is that tells you that that is your
47:23
is that tells you that that is your
47:23
is that tells you that that is your domain. Sometimes takes time to find out
47:26
domain. Sometimes takes time to find out
47:26
domain. Sometimes takes time to find out what you really love but um over the
47:29
what you really love but um over the
47:29
what you really love but um over the time you will find out
47:32
time you will find out
47:32
time you will find out um and sometimes you have to do do
47:34
um and sometimes you have to do do
47:34
um and sometimes you have to do do initially you have to do things to make
47:36
initially you have to do things to make
47:36
initially you have to do things to make living first you make living then over
47:38
living first you make living then over
47:38
living first you make living then over over the years once you settle down then
47:42
over the years once you settle down then
47:42
over the years once you settle down then you figure out what you're passionate
47:44
you figure out what you're passionate
47:44
you figure out what you're passionate about this is something really I don't
47:46
about this is something really I don't
47:46
about this is something really I don't know the answer there's I don't think
47:48
know the answer there's I don't think
47:48
know the answer there's I don't think there's any
47:50
there's any
47:50
there's any test for that but if you're talking
47:53
test for that but if you're talking
47:53
test for that but if you're talking about the technical domain And that
47:55
about the technical domain And that
47:55
about the technical domain And that sometimes also
47:58
sometimes also
47:58
sometimes also technical domain is easy to find out
47:59
technical domain is easy to find out
47:59
technical domain is easy to find out what you're passionate about because
48:01
what you're passionate about because
48:01
what you're passionate about because question is do you like math? Do you
48:03
question is do you like math? Do you
48:03
question is do you like math? Do you like solving puzzles problems or you are
48:06
like solving puzzles problems or you are
48:06
like solving puzzles problems or you are more about
48:08
more about
48:08
more about art and be creative and that's where it
48:11
art and be creative and that's where it
48:11
art and be creative and that's where it you or you are more about people person
48:13
you or you are more about people person
48:13
you or you are more about people person or you're not people person. If you are
48:15
or you're not people person. If you are
48:15
or you're not people person. If you are a people person maybe you want to go in
48:17
a people person maybe you want to go in
48:17
a people person maybe you want to go in leadership and management. If you like
48:19
leadership and management. If you like
48:19
leadership and management. If you like more crafting art, you may want to
48:21
more crafting art, you may want to
48:21
more crafting art, you may want to become more project management side than
48:23
become more project management side than
48:23
become more project management side than the coding side. If you like to really
48:26
the coding side. If you like to really
48:26
the coding side. If you like to really write code and solve problems and all
48:29
write code and solve problems and all
48:29
write code and solve problems and all that, then you want to become a maybe
48:31
that, then you want to become a maybe
48:31
that, then you want to become a maybe engineer. That's that's how you find out
48:33
engineer. That's that's how you find out
48:33
engineer. That's that's how you find out really. Um I don't know about there's a
48:36
really. Um I don't know about there's a
48:36
really. Um I don't know about there's a growing skills there's a lot of platform
48:37
growing skills there's a lot of platform
48:37
growing skills there's a lot of platform as I said C# corner is something you can
48:40
as I said C# corner is something you can
48:40
as I said C# corner is something you can learn every day. Now we are adding more
48:42
learn every day. Now we are adding more
48:42
learn every day. Now we are adding more skills there, challenges there, learning
48:44
skills there, challenges there, learning
48:44
skills there, challenges there, learning there. Check that out. Um there's a lot
48:47
there. Check that out. Um there's a lot
48:47
there. Check that out. Um there's a lot of platforms like that.
48:57
Which certifications can we do towards
48:59
Which certifications can we do towards
48:59
Which certifications can we do towards AI? Ramas Saga asked again. Um right now
49:02
AI? Ramas Saga asked again. Um right now
49:02
AI? Ramas Saga asked again. Um right now the certifications very loose. It's done
49:05
the certifications very loose. It's done
49:05
the certifications very loose. It's done by the companies, right? Um it's better
49:09
by the companies, right? Um it's better
49:09
by the companies, right? Um it's better to in companies it's hard to do
49:12
to in companies it's hard to do
49:12
to in companies it's hard to do certification by companies right now
49:14
certification by companies right now
49:14
certification by companies right now because they are just teaching you their
49:15
because they are just teaching you their
49:15
because they are just teaching you their own their own products
49:19
own their own products
49:20
own their own products but uh as I said we have check out this
49:22
but uh as I said we have check out this
49:22
but uh as I said we have check out this website viber
49:25
website viber
49:25
website viber on demand and we have two certifications
49:28
on demand and we have two certifications
49:28
on demand and we have two certifications coming up
49:30
coming up
49:30
coming up um one is certified prompt engineer
49:34
um one is certified prompt engineer
49:34
um one is certified prompt engineer and certified vibe coder
49:37
and certified vibe coder
49:37
and certified vibe coder These are two simple certifications 10
49:40
These are two simple certifications 10
49:40
These are two simple certifications 10 hours each. I guarantee you that they
49:43
hours each. I guarantee you that they
49:43
hours each. I guarantee you that they will change your life. You will build
49:46
will change your life. You will build
49:46
will change your life. You will build software in
49:48
software in
49:48
software in minutes not even hours. You can build a
49:50
minutes not even hours. You can build a
49:50
minutes not even hours. You can build a complete software fully functional
49:53
complete software fully functional
49:53
complete software fully functional website app in few hours rather than
49:57
website app in few hours rather than
49:58
website app in few hours rather than that used to take six months and
49:59
that used to take six months and
49:59
that used to take six months and thousands of dollars and four five
50:01
thousands of dollars and four five
50:02
thousands of dollars and four five people working. Now using VIP coding and
50:04
people working. Now using VIP coding and
50:04
people working. Now using VIP coding and prompt engineering you can build that in
50:07
prompt engineering you can build that in
50:07
prompt engineering you can build that in hours. We are already doing that. So
50:11
hours. We are already doing that. So
50:11
hours. We are already doing that. So definitely it's worth checking out these
50:13
definitely it's worth checking out these
50:13
definitely it's worth checking out these trainings.
50:21
What is the difference data scientist ML
50:23
What is the difference data scientist ML
50:23
What is the difference data scientist ML engineers? So data science they always
50:25
engineers? So data science they always
50:25
engineers? So data science they always scientists they are almost like they
50:27
scientists they are almost like they
50:27
scientists they are almost like they work with data more. So when when you
50:29
work with data more. So when when you
50:29
work with data more. So when when you think of AI especially generative AI
50:33
think of AI especially generative AI
50:33
think of AI especially generative AI generative AI what it is it's an AI that
50:36
generative AI what it is it's an AI that
50:36
generative AI what it is it's an AI that generates new content.
50:39
generates new content.
50:39
generates new content. So if you say you go to you know AI and
50:42
So if you say you go to you know AI and
50:42
So if you say you go to you know AI and say you go to chat GPT and they say
50:45
say you go to chat GPT and they say
50:45
say you go to chat GPT and they say create me an email. How do you create an
50:48
create me an email. How do you create an
50:48
create me an email. How do you create an email to join a new office whatever or
50:51
email to join a new office whatever or
50:51
email to join a new office whatever or you can say you know thank you email or
50:53
you can say you know thank you email or
50:53
you can say you know thank you email or you can say
50:55
you can say
50:56
you can say write me a code all these things. So
50:58
write me a code all these things. So
50:58
write me a code all these things. So when you tell this to AI
51:03
when you tell this to AI
51:03
when you tell this to AI the way AI work is goes to something
51:05
the way AI work is goes to something
51:05
the way AI work is goes to something called LLM. LLM is large language marl
51:08
called LLM. LLM is large language marl
51:08
called LLM. LLM is large language marl that is the brain behind AI that is the
51:10
that is the brain behind AI that is the
51:10
that is the brain behind AI that is the AI itself LLM is similar to our human
51:13
AI itself LLM is similar to our human
51:13
AI itself LLM is similar to our human brain okay it's exactly like that
51:15
brain okay it's exactly like that
51:15
brain okay it's exactly like that designed like that the way human brain
51:18
designed like that the way human brain
51:18
designed like that the way human brain store information the way human brain
51:20
store information the way human brain
51:20
store information the way human brain thinks that's that's the LLM is copied
51:23
thinks that's that's the LLM is copied
51:23
thinks that's that's the LLM is copied after
51:24
after
51:24
after so that is filled with a lot of data and
51:27
so that is filled with a lot of data and
51:27
so that is filled with a lot of data and semantics and meanings
51:30
semantics and meanings
51:30
semantics and meanings and that data before it comes in LLM it
51:34
and that data before it comes in LLM it
51:34
and that data before it comes in LLM it has to be cleansed Data has to be clean.
51:37
has to be cleansed Data has to be clean.
51:37
has to be cleansed Data has to be clean. Data have to make sure it's clean. Make
51:39
Data have to make sure it's clean. Make
51:39
Data have to make sure it's clean. Make sure it's good. Make sure it makes
51:41
sure it's good. Make sure it makes
51:41
sure it's good. Make sure it makes sense. You cannot put junk in there. If
51:43
sense. You cannot put junk in there. If
51:43
sense. You cannot put junk in there. If you put junk in LLM, your AI will
51:46
you put junk in LLM, your AI will
51:46
you put junk in LLM, your AI will generate LLM. That's why AI also had
51:49
generate LLM. That's why AI also had
51:49
generate LLM. That's why AI also had some problems. That's why prompt
51:50
some problems. That's why prompt
51:50
some problems. That's why prompt engineering becomes very important skill
51:53
engineering becomes very important skill
51:53
engineering becomes very important skill because AI is not always right.
51:55
because AI is not always right.
51:55
because AI is not always right. Especially generative AI. AI is as good
51:58
Especially generative AI. AI is as good
51:58
Especially generative AI. AI is as good as its data. So the people who make sure
52:01
as its data. So the people who make sure
52:01
as its data. So the people who make sure that the data is coming, data is clean,
52:05
that the data is coming, data is clean,
52:05
that the data is coming, data is clean, data rel semantics are right, data
52:08
data rel semantics are right, data
52:08
data rel semantics are right, data relationships are right, data modeling
52:11
relationships are right, data modeling
52:11
relationships are right, data modeling is right, data training is right. Those
52:14
is right, data training is right. Those
52:14
is right, data training is right. Those are the people who are data scientists.
52:18
are the people who are data scientists.
52:18
are the people who are data scientists. For that you need statistics and
52:20
For that you need statistics and
52:20
For that you need statistics and mathematical skills with SQL data almost
52:25
mathematical skills with SQL data almost
52:25
mathematical skills with SQL data almost like these guys work in data side on
52:28
like these guys work in data side on
52:28
like these guys work in data side on databases with Python is also you need
52:30
databases with Python is also you need
52:30
databases with Python is also you need Python skill
52:33
Python skill
52:33
Python skill ML engineers or machine learning
52:34
ML engineers or machine learning
52:34
ML engineers or machine learning engineers are also they work more not on
52:37
engineers are also they work more not on
52:37
engineers are also they work more not on data side data is already there now they
52:40
data side data is already there now they
52:40
data side data is already there now they work on more training the data machine
52:43
work on more training the data machine
52:43
work on more training the data machine learning part using different libraries
52:46
learning part using different libraries
52:46
learning part using different libraries so that's a little bit difference there
52:48
so that's a little bit difference there
52:48
so that's a little bit difference there but both are very technical skills.
52:58
Data analyst, data scientist, data
53:00
Data analyst, data scientist, data
53:00
Data analyst, data scientist, data engineers, they're all these are very um
53:04
engineers, they're all these are very um
53:04
engineers, they're all these are very um close related words, right? Data
53:06
close related words, right? Data
53:06
close related words, right? Data analysis does analysis of the data.
53:09
analysis does analysis of the data.
53:09
analysis does analysis of the data. Scientist does what I just explained.
53:11
Scientist does what I just explained.
53:11
Scientist does what I just explained. Engineer also does build something
53:13
Engineer also does build something
53:14
Engineer also does build something around that. Um you can just ask this
53:17
around that. Um you can just ask this
53:17
around that. Um you can just ask this question to chat GPD to be honest that
53:19
question to chat GPD to be honest that
53:19
question to chat GPD to be honest that will answer better way and you can get
53:22
will answer better way and you can get
53:22
will answer better way and you can get into more details.
53:26
Fullstack developer yes listen fullstack
53:28
Fullstack developer yes listen fullstack
53:28
Fullstack developer yes listen fullstack developer will always be in demand but
53:30
developer will always be in demand but
53:30
developer will always be in demand but these days the way AI is doing it AI can
53:34
these days the way AI is doing it AI can
53:34
these days the way AI is doing it AI can do a lot of fullstack development too. I
53:36
do a lot of fullstack development too. I
53:36
do a lot of fullstack development too. I don't see five five years even three
53:39
don't see five five years even three
53:39
don't see five five years even three years or two three years later you will
53:41
years or two three years later you will
53:41
years or two three years later you will see that AI is building the full stack
53:44
see that AI is building the full stack
53:44
see that AI is building the full stack applications
53:46
applications
53:46
applications the demand will still be there because
53:50
the demand will still be there because
53:50
the demand will still be there because AI can do some things there's always
53:52
AI can do some things there's always
53:52
AI can do some things there's always going to be problems some expert needs
53:54
going to be problems some expert needs
53:54
going to be problems some expert needs to review the code the project the
53:56
to review the code the project the
53:56
to review the code the project the architecture there's always going to be
53:59
architecture there's always going to be
53:59
architecture there's always going to be demand
54:00
demand
54:00
demand um for first tech developers so I'm not
54:04
um for first tech developers so I'm not
54:04
um for first tech developers so I'm not saying it's going away anything anywhere
54:05
saying it's going away anything anywhere
54:06
saying it's going away anything anywhere very soon. Uh but if you learn those
54:10
very soon. Uh but if you learn those
54:10
very soon. Uh but if you learn those tools, vibe coding tools, learn prompt
54:13
tools, vibe coding tools, learn prompt
54:13
tools, vibe coding tools, learn prompt engineering, you can build fullstep
54:16
engineering, you can build fullstep
54:16
engineering, you can build fullstep applications in like few hours now or
54:19
applications in like few hours now or
54:19
applications in like few hours now or even less minutes. I can literally go
54:21
even less minutes. I can literally go
54:21
even less minutes. I can literally go today in 5 minutes I can build a
54:24
today in 5 minutes I can build a
54:24
today in 5 minutes I can build a complete application right it will have
54:26
complete application right it will have
54:26
complete application right it will have a database. We are actually building
54:28
a database. We are actually building
54:28
a database. We are actually building something a tool called sharp coder. So
54:31
something a tool called sharp coder. So
54:32
something a tool called sharp coder. So it's not launched yet. It's coming in
54:34
it's not launched yet. It's coming in
54:34
it's not launched yet. It's coming in beta soon called sharpcoder.ai.
54:37
beta soon called sharpcoder.ai.
54:37
beta soon called sharpcoder.ai. It's our AI tool where you can tell it
54:40
It's our AI tool where you can tell it
54:40
It's our AI tool where you can tell it to build. It will build the it'll create
54:42
to build. It will build the it'll create
54:42
to build. It will build the it'll create your database. It'll create your data
54:44
your database. It'll create your data
54:44
your database. It'll create your data business logic. It'll create all
54:46
business logic. It'll create all
54:46
business logic. It'll create all everything in your full application just
54:49
everything in your full application just
54:49
everything in your full application just in 10 minutes.
54:59
Okay. Great questions guys. Great
55:01
Okay. Great questions guys. Great
55:01
Okay. Great questions guys. Great questions. As a fresher, which is the
55:03
questions. As a fresher, which is the
55:03
questions. As a fresher, which is the best domain to choose, data analytics or
55:06
best domain to choose, data analytics or
55:06
best domain to choose, data analytics or data science? Um, data science is
55:09
data science? Um, data science is
55:09
data science? Um, data science is harder, but that's in more that's going
55:11
harder, but that's in more that's going
55:11
harder, but that's in more that's going to get you more out of the if you're
55:13
to get you more out of the if you're
55:13
to get you more out of the if you're trying to make more money. Data science
55:16
trying to make more money. Data science
55:16
trying to make more money. Data science is the the way to go. Data analy
55:20
is the the way to go. Data analy
55:20
is the the way to go. Data analy analytics is a little bit easier side um
55:23
analytics is a little bit easier side um
55:23
analytics is a little bit easier side um and less salary. You'll make all
55:26
and less salary. You'll make all
55:26
and less salary. You'll make all remember I don't know if you guys heard
55:27
remember I don't know if you guys heard
55:27
remember I don't know if you guys heard that. Oh, Meta hired somebody from
55:32
that. Oh, Meta hired somebody from
55:32
that. Oh, Meta hired somebody from OpenAI and paid them $100 million.
55:36
OpenAI and paid them $100 million.
55:36
OpenAI and paid them $100 million. These guys are getting millions of law
55:37
These guys are getting millions of law
55:37
These guys are getting millions of law salaries right now. They're all a lot of
55:40
salaries right now. They're all a lot of
55:40
salaries right now. They're all a lot of them are data scientists.
55:53
Okay guys, any more questions we're
55:55
Okay guys, any more questions we're
55:55
Okay guys, any more questions we're taking? Can prompt engineering help in
55:57
taking? Can prompt engineering help in
55:57
taking? Can prompt engineering help in DevOps automation? Yes, prompt
56:01
DevOps automation? Yes, prompt
56:01
DevOps automation? Yes, prompt engineering definitely can help in
56:02
engineering definitely can help in
56:02
engineering definitely can help in DevOps automation. DevOps operation is
56:05
DevOps automation. DevOps operation is
56:06
DevOps automation. DevOps operation is much easier task. It was already
56:07
much easier task. It was already
56:07
much easier task. It was already automated before prompt engineering,
56:09
automated before prompt engineering,
56:09
automated before prompt engineering, right? You just set up a CI/CD pipeline
56:12
right? You just set up a CI/CD pipeline
56:12
right? You just set up a CI/CD pipeline with GitHub or any other tools. This
56:15
with GitHub or any other tools. This
56:15
with GitHub or any other tools. This DevOps was already done. Um DevOps is
56:19
DevOps was already done. Um DevOps is
56:19
DevOps was already done. Um DevOps is something it was already automated. You
56:21
something it was already automated. You
56:21
something it was already automated. You don't really need prompt engineering,
56:22
don't really need prompt engineering,
56:22
don't really need prompt engineering, but it can definitely help. Yes.
56:30
[Music]
56:36
What are the best real world AI projects
56:39
What are the best real world AI projects
56:39
What are the best real world AI projects I can build to stand out in interviews?
56:43
I can build to stand out in interviews?
56:43
I can build to stand out in interviews? Uh, it really depends on the interview,
56:45
Uh, it really depends on the interview,
56:45
Uh, it really depends on the interview, right? So if depend on the company
56:48
right? So if depend on the company
56:48
right? So if depend on the company there's you can't really tell if if I'm
56:50
there's you can't really tell if if I'm
56:50
there's you can't really tell if if I'm a I'm a company hiring somebody
56:55
a I'm a company hiring somebody
56:55
a I'm a company hiring somebody um you know to build my front end I will
56:59
um you know to build my front end I will
56:59
um you know to build my front end I will ask you how to use vibe coding using
57:03
ask you how to use vibe coding using
57:03
ask you how to use vibe coding using these which tools have you used right so
57:07
these which tools have you used right so
57:07
these which tools have you used right so if I'm hiring somebody from the depends
57:10
if I'm hiring somebody from the depends
57:10
if I'm hiring somebody from the depends on what my goals are if company's hiring
57:13
on what my goals are if company's hiring
57:13
on what my goals are if company's hiring um for a project that has anything to do
57:16
um for a project that has anything to do
57:16
um for a project that has anything to do with health care. So they want to see if
57:19
with health care. So they want to see if
57:19
with health care. So they want to see if you've done anything in that space. I
57:21
you've done anything in that space. I
57:21
you've done anything in that space. I mean you're a student to be honest. So
57:23
mean you're a student to be honest. So
57:23
mean you're a student to be honest. So they don't expect much
57:25
they don't expect much
57:26
they don't expect much as far as domain.
57:28
as far as domain.
57:28
as far as domain. All they want to see is what project you
57:31
All they want to see is what project you
57:31
All they want to see is what project you have done, how detailed and how much
57:32
have done, how detailed and how much
57:32
have done, how detailed and how much knowledge you have about that project.
57:36
knowledge you have about that project.
57:36
knowledge you have about that project. And that's what I would expect if you
57:38
And that's what I would expect if you
57:38
And that's what I would expect if you are a student.
57:41
are a student.
57:41
are a student. Um so it could be any project to be
57:43
Um so it could be any project to be
57:43
Um so it could be any project to be honest. There's no specific real world
57:45
honest. There's no specific real world
57:45
honest. There's no specific real world example. I would say build a project
57:48
example. I would say build a project
57:48
example. I would say build a project which you
57:51
which you
57:51
which you you are passionate about which you love
57:53
you are passionate about which you love
57:53
you are passionate about which you love to build which you can get more into it.
57:55
to build which you can get more into it.
57:55
to build which you can get more into it. you can more in did death you can do
57:57
you can more in did death you can do
57:58
you can more in did death you can do more lot more with it rather than
58:00
more lot more with it rather than
58:00
more lot more with it rather than building something thinking like what
58:02
building something thinking like what
58:02
building something thinking like what company is going to ask me right so
58:06
company is going to ask me right so
58:06
company is going to ask me right so that's what I would think
58:10
that's what I would think
58:10
that's what I would think and you know when we I'm interviewing I
58:12
and you know when we I'm interviewing I
58:12
and you know when we I'm interviewing I don't interview them what I ask I
58:14
don't interview them what I ask I
58:14
don't interview them what I ask I interview what you have done show me how
58:16
interview what you have done show me how
58:16
interview what you have done show me how did you do that how did you solve a
58:18
did you do that how did you solve a
58:18
did you do that how did you solve a problem that is the skill I really want
58:20
problem that is the skill I really want
58:20
problem that is the skill I really want to I like to for more focus on how did
58:24
to I like to for more focus on how did
58:24
to I like to for more focus on how did you solve the problem. What are the
58:26
you solve the problem. What are the
58:26
you solve the problem. What are the challenges came? What is your solution?
58:29
challenges came? What is your solution?
58:29
challenges came? What is your solution? How did you come up with the solution?
58:30
How did you come up with the solution?
58:30
How did you come up with the solution? Is this the best solution? What is the
58:32
Is this the best solution? What is the
58:32
Is this the best solution? What is the quality of your code? What is the
58:34
quality of your code? What is the
58:34
quality of your code? What is the quality of your applications? What is
58:35
quality of your applications? What is
58:36
quality of your applications? What is the UI UX experience?
58:39
the UI UX experience?
58:39
the UI UX experience? Also, paying attention to UIXUX
58:41
Also, paying attention to UIXUX
58:41
Also, paying attention to UIXUX experience is very important guys. I see
58:44
experience is very important guys. I see
58:44
experience is very important guys. I see a lot of programmers, developers,
58:46
a lot of programmers, developers,
58:46
a lot of programmers, developers, coders, they don't pay much much
58:49
coders, they don't pay much much
58:49
coders, they don't pay much much attention to co UIUX and that's not
58:53
attention to co UIUX and that's not
58:53
attention to co UIUX and that's not good.
58:54
good.
58:54
good. um if you can build some UIUX and that's
58:56
um if you can build some UIUX and that's
58:56
um if you can build some UIUX and that's terrible that's not good. So as a
59:00
terrible that's not good. So as a
59:00
terrible that's not good. So as a company I want to see that you
59:01
company I want to see that you
59:01
company I want to see that you understand the fundamentals of UIUX
59:04
understand the fundamentals of UIUX
59:04
understand the fundamentals of UIUX especially you know human experience.
59:14
Okay, great questions. A lot of good
59:16
Okay, great questions. A lot of good
59:16
Okay, great questions. A lot of good questions coming out from you guys. Will
59:20
questions coming out from you guys. Will
59:20
questions coming out from you guys. Will SLM overtake LLM's real world
59:22
SLM overtake LLM's real world
59:22
SLM overtake LLM's real world applications? So yes and no, right? LLM
59:25
applications? So yes and no, right? LLM
59:25
applications? So yes and no, right? LLM has their own roles. SLM definitely have
59:28
has their own roles. SLM definitely have
59:28
has their own roles. SLM definitely have their own roles. But yes, in coming time
59:31
their own roles. But yes, in coming time
59:31
their own roles. But yes, in coming time there's going to be more and more SLMs
59:33
there's going to be more and more SLMs
59:33
there's going to be more and more SLMs because SLM focusing on certain domains,
59:36
because SLM focusing on certain domains,
59:36
because SLM focusing on certain domains, certain databases, certain part of
59:38
certain databases, certain part of
59:38
certain databases, certain part of aspects. They're less costly. They they
59:41
aspects. They're less costly. They they
59:41
aspects. They're less costly. They they can run locally, right? You don't need
59:42
can run locally, right? You don't need
59:42
can run locally, right? You don't need to run them publicly if you want. For
59:45
to run them publicly if you want. For
59:45
to run them publicly if you want. For example, if there's a banking SML, it
59:48
example, if there's a banking SML, it
59:48
example, if there's a banking SML, it will just focus on banking data. So that
59:50
will just focus on banking data. So that
59:50
will just focus on banking data. So that will be in demand more. Yes. So there's
59:53
will be in demand more. Yes. So there's
59:53
will be in demand more. Yes. So there's going to be more need of building,
59:56
going to be more need of building,
59:56
going to be more need of building, maintaining, upgrading SLMs also PTSL,
1:00:01
maintaining, upgrading SLMs also PTSL,
1:00:01
maintaining, upgrading SLMs also PTSL, right? Private tailored SLM C# corner if
1:00:03
right? Private tailored SLM C# corner if
1:00:03
right? Private tailored SLM C# corner if you go there's a lot of content on um
1:00:08
you go there's a lot of content on um
1:00:08
you go there's a lot of content on um SLM. Um John has written a lot of
1:00:10
SLM. Um John has written a lot of
1:00:10
SLM. Um John has written a lot of things. John Goodel is one of our uh key
1:00:14
things. John Goodel is one of our uh key
1:00:14
things. John Goodel is one of our uh key members on C# Corner. So that's another
1:00:17
members on C# Corner. So that's another
1:00:17
members on C# Corner. So that's another advantage. You join C# Corner, you
1:00:19
advantage. You join C# Corner, you
1:00:19
advantage. You join C# Corner, you become MVP, most valuable professional
1:00:22
become MVP, most valuable professional
1:00:22
become MVP, most valuable professional after sudden you start getting exposure
1:00:25
after sudden you start getting exposure
1:00:25
after sudden you start getting exposure to these hundreds of thousands of people
1:00:27
to these hundreds of thousands of people
1:00:28
to these hundreds of thousands of people if not millions. And John actually he's
1:00:31
if not millions. And John actually he's
1:00:31
if not millions. And John actually he's now a big AI guy. He built his AI
1:00:35
now a big AI guy. He built his AI
1:00:35
now a big AI guy. He built his AI company called Alpine Gate. You can
1:00:37
company called Alpine Gate. You can
1:00:38
company called Alpine Gate. You can search him on LinkedIn. John Godo
1:00:42
search him on LinkedIn. John Godo
1:00:42
search him on LinkedIn. John Godo he he was a C# Corner member years ago
1:00:45
he he was a C# Corner member years ago
1:00:45
he he was a C# Corner member years ago and he joined C# corner he became MVP he
1:00:50
and he joined C# corner he became MVP he
1:00:50
and he joined C# corner he became MVP he then he got a job architect and then
1:00:52
then he got a job architect and then
1:00:52
then he got a job architect and then start his own company so
1:00:56
start his own company so
1:00:56
start his own company so yeah back to your question there's a lot
1:00:58
yeah back to your question there's a lot
1:00:58
yeah back to your question there's a lot more content on C# corner and SLMs small
1:01:01
more content on C# corner and SLMs small
1:01:01
more content on C# corner and SLMs small language models and there's also
1:01:04
language models and there's also
1:01:04
language models and there's also personal models too there's going to be
1:01:07
personal models too there's going to be
1:01:07
personal models too there's going to be uh there's more innovation will happen
1:01:08
uh there's more innovation will happen
1:01:08
uh there's more innovation will happen in these models post in coming time.
1:01:20
Okay. Anything? Well, let's take quick
1:01:22
Okay. Anything? Well, let's take quick
1:01:22
Okay. Anything? Well, let's take quick more questions and then we can u Yeah,
1:01:24
more questions and then we can u Yeah,
1:01:24
more questions and then we can u Yeah, this is great. These are all good
1:01:26
this is great. These are all good
1:01:26
this is great. These are all good questions, guys. It's actually 1:30 a.m.
1:01:29
questions, guys. It's actually 1:30 a.m.
1:01:30
questions, guys. It's actually 1:30 a.m. right now. I'm I'm here in Philadelphia.
1:01:32
right now. I'm I'm here in Philadelphia.
1:01:32
right now. I'm I'm here in Philadelphia. So, it's uh almost 2:00 a.m.
1:01:36
So, it's uh almost 2:00 a.m.
1:01:36
So, it's uh almost 2:00 a.m. All right. Shaker asked question. How is
1:01:38
All right. Shaker asked question. How is
1:01:38
All right. Shaker asked question. How is prompt engineering different than
1:01:39
prompt engineering different than
1:01:39
prompt engineering different than traditional programming? That's a great
1:01:42
traditional programming? That's a great
1:01:42
traditional programming? That's a great question, Shaker. Traditional
1:01:43
question, Shaker. Traditional
1:01:43
question, Shaker. Traditional programming,
1:01:45
programming,
1:01:45
programming, you write code by hand. You know, you
1:01:48
you write code by hand. You know, you
1:01:48
you write code by hand. You know, you learn programming language, you learn
1:01:51
learn programming language, you learn
1:01:51
learn programming language, you learn syntaxes,
1:01:52
syntaxes,
1:01:52
syntaxes, you go to IDE, you go to one of the
1:01:55
you go to IDE, you go to one of the
1:01:55
you go to IDE, you go to one of the tools, you start writing code. Sometimes
1:01:57
tools, you start writing code. Sometimes
1:01:57
tools, you start writing code. Sometimes you can use drag and drop all that. But
1:02:00
you can use drag and drop all that. But
1:02:00
you can use drag and drop all that. But everything you are doing manually in
1:02:03
everything you are doing manually in
1:02:03
everything you are doing manually in prompt engineering.
1:02:05
prompt engineering.
1:02:05
prompt engineering. Um, you are just saying let me show you
1:02:07
Um, you are just saying let me show you
1:02:07
Um, you are just saying let me show you quickly. See if I can share a screen.
1:02:12
Can I share a screen? Simon.
1:02:21
Yep, I can share my screen.
1:02:27
Okay, I'm going to share my screen.
1:02:28
Okay, I'm going to share my screen.
1:02:28
Okay, I'm going to share my screen. That's what prompt engineering is
1:02:30
That's what prompt engineering is
1:02:30
That's what prompt engineering is different, right? Let me see if you see
1:02:33
different, right? Let me see if you see
1:02:33
different, right? Let me see if you see my screen, Simon. Yep.
1:02:36
my screen, Simon. Yep.
1:02:36
my screen, Simon. Yep. So now you guys see my screen
1:02:40
So now you guys see my screen
1:02:40
So now you guys see my screen and
1:02:44
traditional programming you'll go to a
1:02:46
traditional programming you'll go to a
1:02:46
traditional programming you'll go to a tool. Let's say
1:02:49
tool. Let's say
1:02:49
tool. Let's say you'll go to Visual Studio here. I'll
1:02:51
you'll go to Visual Studio here. I'll
1:02:51
you'll go to Visual Studio here. I'll show you quickly.
1:02:54
show you quickly.
1:02:54
show you quickly. And the reason I really want to show you
1:02:56
And the reason I really want to show you
1:02:56
And the reason I really want to show you because
1:02:58
because
1:02:58
because this is how cool if you have not done
1:03:00
this is how cool if you have not done
1:03:00
this is how cool if you have not done prompt engineering and uh not done vive
1:03:04
prompt engineering and uh not done vive
1:03:04
prompt engineering and uh not done vive coding this is a game changer guys.
1:03:09
coding this is a game changer guys.
1:03:09
coding this is a game changer guys. So this is my visual studio here. It's
1:03:12
So this is my visual studio here. It's
1:03:12
So this is my visual studio here. It's loading my project. It's a react project
1:03:15
loading my project. It's a react project
1:03:15
loading my project. It's a react project looks like. I even forgot what project
1:03:17
looks like. I even forgot what project
1:03:17
looks like. I even forgot what project it is.
1:03:23
So regardless this is some code here
1:03:25
So regardless this is some code here
1:03:25
So regardless this is some code here right. So this is traditional coding. If
1:03:28
right. So this is traditional coding. If
1:03:28
right. So this is traditional coding. If I have to make some changes to this the
1:03:31
I have to make some changes to this the
1:03:31
I have to make some changes to this the CSS or JX
1:03:35
I have to type everything by hand right
1:03:40
I have to type everything by hand right
1:03:40
I have to type everything by hand right I have to do all that. But here I have
1:03:43
I have to do all that. But here I have
1:03:43
I have to do all that. But here I have something called in this
1:03:45
something called in this
1:03:46
something called in this something called GitHub copilot. Okay,
1:03:49
something called GitHub copilot. Okay,
1:03:49
something called GitHub copilot. Okay, GitHub copilot can I can just ask
1:03:52
GitHub copilot can I can just ask
1:03:52
GitHub copilot can I can just ask copilot can you change
1:03:56
copilot can you change
1:03:56
copilot can you change can you add a new
1:04:00
can you add a new
1:04:00
can you add a new page that loads
1:04:04
page that loads
1:04:04
page that loads all my
1:04:05
all my
1:04:05
all my all names so there may be a data so this
1:04:09
all names so there may be a data so this
1:04:09
all names so there may be a data so this is what you do prompt engineering you
1:04:10
is what you do prompt engineering you
1:04:10
is what you do prompt engineering you tell AI what to do and it does for you
1:04:14
tell AI what to do and it does for you
1:04:14
tell AI what to do and it does for you don't write code you never write code AI
1:04:17
don't write code you never write code AI
1:04:17
don't write code you never write code AI is writing code for you. This is just
1:04:19
is writing code for you. This is just
1:04:19
is writing code for you. This is just one example but let me show you another
1:04:21
one example but let me show you another
1:04:21
one example but let me show you another big example which is live. So there is
1:04:24
big example which is live. So there is
1:04:24
big example which is live. So there is this tool called Lovable
1:04:27
this tool called Lovable
1:04:27
this tool called Lovable Loveable.dev
1:04:29
Loveable.dev
1:04:29
Loveable.dev and this one guy built this tool in few
1:04:32
and this one guy built this tool in few
1:04:32
and this one guy built this tool in few hours at night. Now this guy he just
1:04:35
hours at night. Now this guy he just
1:04:35
hours at night. Now this guy he just raised $200 million company's worth $1.8
1:04:38
raised $200 million company's worth $1.8
1:04:38
raised $200 million company's worth $1.8 billion. Now billion means B. So this is
1:04:42
billion. Now billion means B. So this is
1:04:42
billion. Now billion means B. So this is a prompt engineer right? I'm going to
1:04:44
a prompt engineer right? I'm going to
1:04:44
a prompt engineer right? I'm going to say,
1:04:46
say,
1:04:46
say, can you
1:04:49
can you
1:04:49
can you build a website for students
1:04:53
build a website for students
1:04:53
build a website for students to chat and ask questions about their
1:04:57
to chat and ask questions about their
1:04:57
to chat and ask questions about their career?
1:05:01
Make it cool looking.
1:05:06
Use
1:05:10
vibrant colors.
1:05:12
vibrant colors.
1:05:12
vibrant colors. Let's see what it does. Let's start with
1:05:14
Let's see what it does. Let's start with
1:05:14
Let's see what it does. Let's start with that. Right? And you can be you can you
1:05:16
that. Right? And you can be you can you
1:05:16
that. Right? And you can be you can you can have a
1:05:18
can have a
1:05:18
can have a little bit spelling mistakes. AI
1:05:20
little bit spelling mistakes. AI
1:05:20
little bit spelling mistakes. AI understands all that. So what this tool
1:05:22
understands all that. So what this tool
1:05:22
understands all that. So what this tool is doing behind the scene is it's
1:05:26
is doing behind the scene is it's
1:05:26
is doing behind the scene is it's actually taking my input breaking down
1:05:28
actually taking my input breaking down
1:05:28
actually taking my input breaking down into these prompts. So this is the
1:05:30
into these prompts. So this is the
1:05:30
into these prompts. So this is the prompt. It took my text
1:05:34
prompt. It took my text
1:05:34
prompt. It took my text and then converting this text to the
1:05:36
and then converting this text to the
1:05:36
and then converting this text to the prompt that AI would understand is this
1:05:38
prompt that AI would understand is this
1:05:38
prompt that AI would understand is this is part of prompt engineering.
1:05:42
is part of prompt engineering.
1:05:42
is part of prompt engineering. Like if I was smart enough, I could have
1:05:44
Like if I was smart enough, I could have
1:05:44
Like if I was smart enough, I could have created this prone myself. So now what
1:05:47
created this prone myself. So now what
1:05:47
created this prone myself. So now what AI is doing, it's calling LLMs
1:05:50
AI is doing, it's calling LLMs
1:05:50
AI is doing, it's calling LLMs which we talked about. Remember LLMs are
1:05:52
which we talked about. Remember LLMs are
1:05:52
which we talked about. Remember LLMs are the brain behind AI. So now right now
1:05:56
the brain behind AI. So now right now
1:05:56
the brain behind AI. So now right now it's sending these prompts to AI and AI
1:05:59
it's sending these prompts to AI and AI
1:05:59
it's sending these prompts to AI and AI is now um you know sometimes you have to
1:06:02
is now um you know sometimes you have to
1:06:02
is now um you know sometimes you have to break down prompts into multiple
1:06:04
break down prompts into multiple
1:06:04
break down prompts into multiple prompts. Sometimes you have to craft in
1:06:07
prompts. Sometimes you have to craft in
1:06:07
prompts. Sometimes you have to craft in different ways.
1:06:09
different ways.
1:06:09
different ways. Um then what it does it's also telling
1:06:12
Um then what it does it's also telling
1:06:12
Um then what it does it's also telling you here which what is it doing it's
1:06:14
you here which what is it doing it's
1:06:14
you here which what is it doing it's also not only getting the code from AI
1:06:17
also not only getting the code from AI
1:06:17
also not only getting the code from AI it's also packaging it's also creating
1:06:20
it's also packaging it's also creating
1:06:20
it's also packaging it's also creating it's all deploying it because everything
1:06:23
it's all deploying it because everything
1:06:23
it's all deploying it because everything you will do from writing code to
1:06:25
you will do from writing code to
1:06:25
you will do from writing code to creating screens designing colors
1:06:28
creating screens designing colors
1:06:28
creating screens designing colors setting CSS HTML
1:06:31
setting CSS HTML
1:06:31
setting CSS HTML building the project fixing the bugs
1:06:34
building the project fixing the bugs
1:06:34
building the project fixing the bugs finding issues
1:06:37
finding issues
1:06:37
finding issues creating graphics logos those icons to
1:06:40
creating graphics logos those icons to
1:06:40
creating graphics logos those icons to then putting on a server, deploying on a
1:06:43
then putting on a server, deploying on a
1:06:43
then putting on a server, deploying on a server or GitHub or somewhere it's doing
1:06:46
server or GitHub or somewhere it's doing
1:06:46
server or GitHub or somewhere it's doing all that right now and this will be done
1:06:49
all that right now and this will be done
1:06:49
all that right now and this will be done in less than less than 10 minutes. So
1:06:52
in less than less than 10 minutes. So
1:06:52
in less than less than 10 minutes. So that's what prompt engineering is while
1:06:55
that's what prompt engineering is while
1:06:55
that's what prompt engineering is while if you an old way traditional
1:06:57
if you an old way traditional
1:06:57
if you an old way traditional programming you have to build this
1:06:59
programming you have to build this
1:06:59
programming you have to build this website it's going to take you months
1:07:01
website it's going to take you months
1:07:01
website it's going to take you months and months things like that right so
1:07:03
and months things like that right so
1:07:03
and months things like that right so think like WordPress right you go to
1:07:05
think like WordPress right you go to
1:07:05
think like WordPress right you go to WordPress
1:07:07
WordPress
1:07:07
WordPress WordPress is you go and say create a
1:07:09
WordPress is you go and say create a
1:07:09
WordPress is you go and say create a website choose this template so
1:07:12
website choose this template so
1:07:12
website choose this template so WordPress what happens there's fixed
1:07:13
WordPress what happens there's fixed
1:07:13
WordPress what happens there's fixed templates already there
1:07:16
templates already there
1:07:16
templates already there um and these fixed templates are
1:07:18
um and these fixed templates are
1:07:18
um and these fixed templates are deployed somewhere WordPress you will
1:07:20
deployed somewhere WordPress you will
1:07:20
deployed somewhere WordPress you will ask you which server to connect to and
1:07:21
ask you which server to connect to and
1:07:22
ask you which server to connect to and you can deploy that your website is done
1:07:24
you can deploy that your website is done
1:07:24
you can deploy that your website is done in you know short period of time but in
1:07:27
in you know short period of time but in
1:07:27
in you know short period of time but in AI here it's actually creating new code
1:07:30
AI here it's actually creating new code
1:07:30
AI here it's actually creating new code for you AI always generative AI it's
1:07:34
for you AI always generative AI it's
1:07:34
for you AI always generative AI it's using generative AI behind the scene it
1:07:37
using generative AI behind the scene it
1:07:37
using generative AI behind the scene it always creates new content it does not
1:07:40
always creates new content it does not
1:07:40
always creates new content it does not copy any content from anywhere so you
1:07:44
copy any content from anywhere so you
1:07:44
copy any content from anywhere so you will not find sometimes it gets the idea
1:07:47
will not find sometimes it gets the idea
1:07:48
will not find sometimes it gets the idea so now you would say how does AI know
1:07:50
so now you would say how does AI know
1:07:50
so now you would say how does AI know what to write code because what OpenAI
1:07:55
what to write code because what OpenAI
1:07:55
what to write code because what OpenAI and other companies what they did is
1:07:56
and other companies what they did is
1:07:56
and other companies what they did is they went to websites all websites
1:07:59
they went to websites all websites
1:07:59
they went to websites all websites they went to books they went to all
1:08:02
they went to books they went to all
1:08:02
they went to books they went to all GitHub code they went to all the
1:08:05
GitHub code they went to all the
1:08:05
GitHub code they went to all the everywhere they could find the data they
1:08:08
everywhere they could find the data they
1:08:08
everywhere they could find the data they went everywhere they almost copy the
1:08:11
went everywhere they almost copy the
1:08:11
went everywhere they almost copy the data and they learned from it that's
1:08:13
data and they learned from it that's
1:08:13
data and they learned from it that's where data scientists came in they got
1:08:15
where data scientists came in they got
1:08:15
where data scientists came in they got all the data they look at the data clean
1:08:18
all the data they look at the data clean
1:08:18
all the data they look at the data clean the data made a useful day all those
1:08:20
the data made a useful day all those
1:08:20
the data made a useful day all those work that took them years and that also
1:08:23
work that took them years and that also
1:08:23
work that took them years and that also took them I think open AI cost them
1:08:26
took them I think open AI cost them
1:08:26
took them I think open AI cost them almost if I not wrong maybe $200 million
1:08:30
almost if I not wrong maybe $200 million
1:08:30
almost if I not wrong maybe $200 million to $500 million to build GPT some of the
1:08:34
to $500 million to build GPT some of the
1:08:34
to $500 million to build GPT some of the old models GPT models each model cost
1:08:37
old models GPT models each model cost
1:08:37
old models GPT models each model cost them more than $und00 million okay so
1:08:41
them more than $und00 million okay so
1:08:41
them more than $und00 million okay so look at this thing right so I use prompt
1:08:43
look at this thing right so I use prompt
1:08:43
look at this thing right so I use prompt now within 10 minutes or 5 minutes my
1:08:46
now within 10 minutes or 5 minutes my
1:08:46
now within 10 minutes or 5 minutes my website is ready your carrier starts
1:08:48
website is ready your carrier starts
1:08:48
website is ready your carrier starts here Start chatting, explore carriers,
1:08:52
here Start chatting, explore carriers,
1:08:52
here Start chatting, explore carriers, right? It's all done here.
1:08:55
right? It's all done here.
1:08:55
right? It's all done here. Look, it also shows how it looks like,
1:08:58
Look, it also shows how it looks like,
1:08:58
Look, it also shows how it looks like, right? Trusted by thousands.
1:09:01
right? Trusted by thousands.
1:09:02
right? Trusted by thousands. There's a real time chat. What are the
1:09:03
There's a real time chat. What are the
1:09:03
There's a real time chat. What are the features? Unlock. And I can go and
1:09:06
features? Unlock. And I can go and
1:09:06
features? Unlock. And I can go and change it right now. say,
1:09:10
change it right now. say,
1:09:10
change it right now. say, [Music]
1:09:11
[Music]
1:09:12
[Music] "Can you change
1:09:14
"Can you change
1:09:14
"Can you change the hero
1:09:17
the hero
1:09:17
the hero title to
1:09:19
title to
1:09:19
title to welcome students?"
1:09:24
Right? So, I say, you know, I'm going to
1:09:26
Right? So, I say, you know, I'm going to
1:09:26
Right? So, I say, you know, I'm going to change this and you can change anything
1:09:28
change this and you can change anything
1:09:28
change this and you can change anything here. You can just talk to it. Um, but
1:09:31
here. You can just talk to it. Um, but
1:09:31
here. You can just talk to it. Um, but it, look at this. It actually told you
1:09:33
it, look at this. It actually told you
1:09:33
it, look at this. It actually told you what it does, right? It created this
1:09:35
what it does, right? It created this
1:09:36
what it does, right? It created this this look right. So look at it changed
1:09:38
this look right. So look at it changed
1:09:38
this look right. So look at it changed to my
1:09:40
to my
1:09:40
to my it just changed my text to welcome
1:09:42
it just changed my text to welcome
1:09:42
it just changed my text to welcome students your carrier awaits right you
1:09:44
students your carrier awaits right you
1:09:44
students your carrier awaits right you can change whatever you want you can
1:09:45
can change whatever you want you can
1:09:45
can change whatever you want you can just add more buttons add code behind
1:09:48
just add more buttons add code behind
1:09:48
just add more buttons add code behind this start chatting so right now what's
1:09:51
this start chatting so right now what's
1:09:51
this start chatting so right now what's happening is start chatting when you
1:09:52
happening is start chatting when you
1:09:52
happening is start chatting when you click there's no code here I can also go
1:09:54
click there's no code here I can also go
1:09:54
click there's no code here I can also go and add coding there behind so things
1:09:57
and add coding there behind so things
1:09:57
and add coding there behind so things like that now this has limitations this
1:10:01
like that now this has limitations this
1:10:01
like that now this has limitations this tool has limitations it cannot do lot of
1:10:04
tool has limitations it cannot do lot of
1:10:04
tool has limitations it cannot do lot of things behind the scene let's say you
1:10:06
things behind the scene let's say you
1:10:06
things behind the scene let's say you say Oh, send an email. It will not do
1:10:08
say Oh, send an email. It will not do
1:10:08
say Oh, send an email. It will not do that. It's only creating the UI in the
1:10:11
that. It's only creating the UI in the
1:10:11
that. It's only creating the UI in the front end to send an email. That's when
1:10:14
front end to send an email. That's when
1:10:14
front end to send an email. That's when you'll have to plug in behind the scene.
1:10:16
you'll have to plug in behind the scene.
1:10:16
you'll have to plug in behind the scene. Maybe some kind of API, maybe some kind
1:10:18
Maybe some kind of API, maybe some kind
1:10:18
Maybe some kind of API, maybe some kind of agent in the future. So, this is all
1:10:21
of agent in the future. So, this is all
1:10:21
of agent in the future. So, this is all start. But point is look what where we
1:10:24
start. But point is look what where we
1:10:24
start. But point is look what where we have come so far that it has created
1:10:27
have come so far that it has created
1:10:27
have come so far that it has created this amazing UI. And by the way, I can
1:10:29
this amazing UI. And by the way, I can
1:10:29
this amazing UI. And by the way, I can take this code project and open in my
1:10:33
take this code project and open in my
1:10:33
take this code project and open in my IDE like VS code or Visual Studio and
1:10:37
IDE like VS code or Visual Studio and
1:10:37
IDE like VS code or Visual Studio and start working on this project from
1:10:39
start working on this project from
1:10:39
start working on this project from there. So hopefully this kind of explain
1:10:41
there. So hopefully this kind of explain
1:10:41
there. So hopefully this kind of explain you that this is all vibe coding. This
1:10:44
you that this is all vibe coding. This
1:10:44
you that this is all vibe coding. This is part of prompt engineing vibe coding.
1:10:46
is part of prompt engineing vibe coding.
1:10:46
is part of prompt engineing vibe coding. And when I said let me also show you
1:10:49
And when I said let me also show you
1:10:49
And when I said let me also show you something. Um well we are already here.
1:10:53
something. Um well we are already here.
1:10:54
something. Um well we are already here. I'm going to share my screen again.
1:11:00
Um,
1:11:02
Um,
1:11:02
Um, so I think you see my screen now. You
1:11:04
so I think you see my screen now. You
1:11:04
so I think you see my screen now. You guys see my screen. I want you to check
1:11:07
guys see my screen. I want you to check
1:11:07
guys see my screen. I want you to check out this Viber on demand. This is the
1:11:10
out this Viber on demand. This is the
1:11:10
out this Viber on demand. This is the create. We just created this website
1:11:12
create. We just created this website
1:11:12
create. We just created this website using Vive coding literally in minutes.
1:11:16
using Vive coding literally in minutes.
1:11:16
using Vive coding literally in minutes. Okay. And you can see there's boot camp
1:11:18
Okay. And you can see there's boot camp
1:11:18
Okay. And you can see there's boot camp here and there's a training here. So we
1:11:22
here and there's a training here. So we
1:11:22
here and there's a training here. So we have these few trainings here. AI and
1:11:24
have these few trainings here. AI and
1:11:24
have these few trainings here. AI and prompt engineering boot camp. It's 10
1:11:26
prompt engineering boot camp. It's 10
1:11:26
prompt engineering boot camp. It's 10 modules, 10 hours. V coding training.
1:11:31
modules, 10 hours. V coding training.
1:11:31
modules, 10 hours. V coding training. Uh JNI for engineering teams. So this is
1:11:33
Uh JNI for engineering teams. So this is
1:11:33
Uh JNI for engineering teams. So this is for teams. They're already software
1:11:35
for teams. They're already software
1:11:35
for teams. They're already software developers. Geni for executive leaders.
1:11:39
developers. Geni for executive leaders.
1:11:39
developers. Geni for executive leaders. Uh and prompt engineering training. So
1:11:41
Uh and prompt engineering training. So
1:11:41
Uh and prompt engineering training. So check out these um
1:11:44
check out these um
1:11:44
check out these um um this is already set here but point is
1:11:46
um this is already set here but point is
1:11:46
um this is already set here but point is that by learning these two skills prompt
1:11:49
that by learning these two skills prompt
1:11:49
that by learning these two skills prompt engineering and V coding you can build
1:11:51
engineering and V coding you can build
1:11:51
engineering and V coding you can build these amazing software in a matter of
1:11:55
these amazing software in a matter of
1:11:55
these amazing software in a matter of minutes and hours rather than months and
1:11:57
minutes and hours rather than months and
1:11:57
minutes and hours rather than months and months. So hopefully
1:12:01
months. So hopefully
1:12:01
months. So hopefully that uh helps you understand what it
1:12:03
that uh helps you understand what it
1:12:03
that uh helps you understand what it means.
1:12:15
Okay guys, I think we'll take a couple
1:12:17
Okay guys, I think we'll take a couple
1:12:17
Okay guys, I think we'll take a couple of more questions. Let's u Simon, let's
1:12:20
of more questions. Let's u Simon, let's
1:12:20
of more questions. Let's u Simon, let's take a few more questions
1:12:23
take a few more questions
1:12:23
take a few more questions and then we can close. These are good
1:12:25
and then we can close. These are good
1:12:25
and then we can close. These are good questions. Amazing. Currently becoming
1:12:28
questions. Amazing. Currently becoming
1:12:28
questions. Amazing. Currently becoming context engineering. What are your
1:12:29
context engineering. What are your
1:12:29
context engineering. What are your thoughts? This is a part of this whole I
1:12:33
thoughts? This is a part of this whole I
1:12:33
thoughts? This is a part of this whole I think prompt engineering. uh if that's
1:12:34
think prompt engineering. uh if that's
1:12:34
think prompt engineering. uh if that's what IB you mean it gets more depth into
1:12:37
what IB you mean it gets more depth into
1:12:37
what IB you mean it gets more depth into details I don't know much about context
1:12:40
details I don't know much about context
1:12:40
details I don't know much about context engineering I'm not expert in that as a
1:12:43
engineering I'm not expert in that as a
1:12:43
engineering I'm not expert in that as a matter of fact I wasn't really much into
1:12:46
matter of fact I wasn't really much into
1:12:46
matter of fact I wasn't really much into AI too until I just start learning like
1:12:48
AI too until I just start learning like
1:12:48
AI too until I just start learning like few months back so I'm like as I know as
1:12:52
few months back so I'm like as I know as
1:12:52
few months back so I'm like as I know as much as you guys know I just know a
1:12:54
much as you guys know I just know a
1:12:54
much as you guys know I just know a little bit more I was not an AI expert
1:12:57
little bit more I was not an AI expert
1:12:57
little bit more I was not an AI expert or engineer I'm just learning prompt
1:12:59
or engineer I'm just learning prompt
1:12:59
or engineer I'm just learning prompt engineering v coding I'm just a
1:13:02
engineering v coding I'm just a
1:13:02
engineering v coding I'm just a traditional programmer like you guys are
1:13:04
traditional programmer like you guys are
1:13:04
traditional programmer like you guys are I just tried C that's the only
1:13:07
I just tried C that's the only
1:13:07
I just tried C that's the only programming language I know C++ VB.NET
1:13:09
programming language I know C++ VB.NET
1:13:10
programming language I know C++ VB.NET net. So I C# is my language uh which I
1:13:13
net. So I C# is my language uh which I
1:13:13
net. So I C# is my language uh which I haven't done a lot of work in but now
1:13:18
haven't done a lot of work in but now
1:13:18
haven't done a lot of work in but now uh can vive coders replace other domain?
1:13:21
uh can vive coders replace other domain?
1:13:21
uh can vive coders replace other domain? I don't know what domain means but I v
1:13:24
I don't know what domain means but I v
1:13:24
I don't know what domain means but I v coders can definitely replace lot of
1:13:26
coders can definitely replace lot of
1:13:26
coders can definitely replace lot of other coders.
1:13:28
other coders.
1:13:28
other coders. So if you are a web coder I don't need a
1:13:30
So if you are a web coder I don't need a
1:13:30
So if you are a web coder I don't need a front-end developer right I just showed
1:13:33
front-end developer right I just showed
1:13:33
front-end developer right I just showed you that
1:13:35
you that
1:13:35
you that if I front-end developer if I hire
1:13:37
if I front-end developer if I hire
1:13:37
if I front-end developer if I hire traditional they will take months and
1:13:40
traditional they will take months and
1:13:40
traditional they will take months and months or at least weeks to build that
1:13:42
months or at least weeks to build that
1:13:42
months or at least weeks to build that UI. If I have a w coder who can build
1:13:45
UI. If I have a w coder who can build
1:13:45
UI. If I have a w coder who can build this in oh use CSS you bootstrap you
1:13:48
this in oh use CSS you bootstrap you
1:13:48
this in oh use CSS you bootstrap you JavaScript use react build this front
1:13:51
JavaScript use react build this front
1:13:51
JavaScript use react build this front end and boom it's already done. Um now
1:13:57
end and boom it's already done. Um now
1:13:57
end and boom it's already done. Um now they should also know how to then fix it
1:13:59
they should also know how to then fix it
1:13:59
they should also know how to then fix it and you know obviously you have to know
1:14:00
and you know obviously you have to know
1:14:00
and you know obviously you have to know a little bit more about it.
1:14:10
uh is fine-tuning in LLM prompt
1:14:13
uh is fine-tuning in LLM prompt
1:14:13
uh is fine-tuning in LLM prompt engineering fine-tuning in LLM is not
1:14:15
engineering fine-tuning in LLM is not
1:14:15
engineering fine-tuning in LLM is not prompt engineering fine-tuning is part
1:14:17
prompt engineering fine-tuning is part
1:14:17
prompt engineering fine-tuning is part of your your you know LLM this a IML
1:14:22
of your your you know LLM this a IML
1:14:22
of your your you know LLM this a IML yeah fine-tuning means it can be
1:14:25
yeah fine-tuning means it can be
1:14:25
yeah fine-tuning means it can be finetuning means is there's automation
1:14:27
finetuning means is there's automation
1:14:27
finetuning means is there's automation and finetuning right finetuning means
1:14:29
and finetuning right finetuning means
1:14:29
and finetuning right finetuning means when you send feedback to
1:14:34
when you send feedback to
1:14:34
when you send feedback to this LLM that's fine tuning it does
1:14:36
this LLM that's fine tuning it does
1:14:36
this LLM that's fine tuning it does fixes learn from it does that but it
1:14:39
fixes learn from it does that but it
1:14:39
fixes learn from it does that but it also can be fine tuning done by
1:14:41
also can be fine tuning done by
1:14:41
also can be fine tuning done by engineering side. So there are two parts
1:14:44
engineering side. So there are two parts
1:14:44
engineering side. So there are two parts to that. Um it's not really part of
1:14:47
to that. Um it's not really part of
1:14:48
to that. Um it's not really part of prompt engineering because you can tell
1:14:50
prompt engineering because you can tell
1:14:50
prompt engineering because you can tell but that's like you're already making
1:14:52
but that's like you're already making
1:14:52
but that's like you're already making dialogue with it's a part of LLM's
1:14:54
dialogue with it's a part of LLM's
1:14:54
dialogue with it's a part of LLM's functionality. That's one of the what it
1:14:56
functionality. That's one of the what it
1:14:56
functionality. That's one of the what it does. If if you provide more feedback to
1:15:00
does. If if you provide more feedback to
1:15:00
does. If if you provide more feedback to LLM, it will take that it will learn
1:15:02
LLM, it will take that it will learn
1:15:02
LLM, it will take that it will learn from it. It will try to fix it. So LLM
1:15:04
from it. It will try to fix it. So LLM
1:15:04
from it. It will try to fix it. So LLM may be answering right. Say if you say
1:15:08
may be answering right. Say if you say
1:15:08
may be answering right. Say if you say um capital of India is Delhi you ask you
1:15:12
um capital of India is Delhi you ask you
1:15:12
um capital of India is Delhi you ask you go to chat GPT and ask it say capital of
1:15:14
go to chat GPT and ask it say capital of
1:15:14
go to chat GPT and ask it say capital of India is Delhi it will say no you say
1:15:17
India is Delhi it will say no you say
1:15:17
India is Delhi it will say no you say what is the capital of India that's what
1:15:19
what is the capital of India that's what
1:15:19
what is the capital of India that's what it say will say Delhi now
1:15:24
it say will say Delhi now
1:15:24
it say will say Delhi now if you say capital of India is not Delhi
1:15:27
if you say capital of India is not Delhi
1:15:27
if you say capital of India is not Delhi it's Chennai
1:15:29
it's Chennai
1:15:29
it's Chennai first it will learn from say it will see
1:15:31
first it will learn from say it will see
1:15:31
first it will learn from say it will see oh there's 10,000 places IC reference is
1:15:34
oh there's 10,000 places IC reference is
1:15:34
oh there's 10,000 places IC reference is India's capital is Delhi you are telling
1:15:37
India's capital is Delhi you are telling
1:15:37
India's capital is Delhi you are telling me Chennai so it will probably reject
1:15:39
me Chennai so it will probably reject
1:15:39
me Chennai so it will probably reject that but if 100,000 people tell same
1:15:42
that but if 100,000 people tell same
1:15:42
that but if 100,000 people tell same thing it will fine-tune and learn it and
1:15:45
thing it will fine-tune and learn it and
1:15:45
thing it will fine-tune and learn it and fix that behind the scene and if
1:15:48
fix that behind the scene and if
1:15:48
fix that behind the scene and if somebody ask later it'll say capital of
1:15:50
somebody ask later it'll say capital of
1:15:50
somebody ask later it'll say capital of India Chennai right so that process of
1:15:55
India Chennai right so that process of
1:15:55
India Chennai right so that process of itself learning
1:16:00
[Music]
1:16:08
Is the MNC's expect the fresher should
1:16:12
Is the MNC's expect the fresher should
1:16:12
Is the MNC's expect the fresher should take part in any of on hackathon during
1:16:15
take part in any of on hackathon during
1:16:15
take part in any of on hackathon during the placement or whether the hackathon
1:16:17
the placement or whether the hackathon
1:16:18
the placement or whether the hackathon participants is more important in
1:16:19
participants is more important in
1:16:19
participants is more important in resume?
1:16:21
resume?
1:16:21
resume? Um I don't think MNC will have
1:16:24
Um I don't think MNC will have
1:16:24
Um I don't think MNC will have hackathons for placements because they
1:16:26
hackathons for placements because they
1:16:26
hackathons for placements because they just don't have time and they don't want
1:16:30
just don't have time and they don't want
1:16:30
just don't have time and they don't want to you to participate in that. But if
1:16:32
to you to participate in that. But if
1:16:32
to you to participate in that. But if you have already participated in a
1:16:35
you have already participated in a
1:16:35
you have already participated in a hackathon
1:16:36
hackathon
1:16:36
hackathon that helps but some companies what they
1:16:40
that helps but some companies what they
1:16:40
that helps but some companies what they do now we have a company working with us
1:16:43
do now we have a company working with us
1:16:43
do now we have a company working with us they agreed to work with us say if you
1:16:45
they agreed to work with us say if you
1:16:45
they agreed to work with us say if you do hackathons
1:16:47
do hackathons
1:16:47
do hackathons you select some candidates we can
1:16:49
you select some candidates we can
1:16:49
you select some candidates we can interview them or maybe we'll come and
1:16:50
interview them or maybe we'll come and
1:16:50
interview them or maybe we'll come and judge them that's what we are doing with
1:16:52
judge them that's what we are doing with
1:16:52
judge them that's what we are doing with hack India in coming time next year hack
1:16:55
hack India in coming time next year hack
1:16:55
hack India in coming time next year hack India our goal is that companies MNC
1:16:59
India our goal is that companies MNC
1:16:59
India our goal is that companies MNC companies will particip will be The
1:17:04
companies will particip will be The
1:17:04
companies will particip will be The sponsors also the judges also the
1:17:07
sponsors also the judges also the
1:17:07
sponsors also the judges also the interviewers part of these hackathons
1:17:09
interviewers part of these hackathons
1:17:09
interviewers part of these hackathons reviewing the projects because now they
1:17:12
reviewing the projects because now they
1:17:12
reviewing the projects because now they know what you have built and they they
1:17:14
know what you have built and they they
1:17:14
know what you have built and they they know exactly what kind of person they
1:17:16
know exactly what kind of person they
1:17:16
know exactly what kind of person they want to hire. They will also provide the
1:17:19
want to hire. They will also provide the
1:17:19
want to hire. They will also provide the problems. What we are working with them
1:17:21
problems. What we are working with them
1:17:21
problems. What we are working with them is that if there's MNC company working
1:17:24
is that if there's MNC company working
1:17:24
is that if there's MNC company working in a banking domain, we want them to
1:17:28
in a banking domain, we want them to
1:17:28
in a banking domain, we want them to give us banking problem. So the students
1:17:31
give us banking problem. So the students
1:17:31
give us banking problem. So the students who are participating hackathon can now
1:17:33
who are participating hackathon can now
1:17:34
who are participating hackathon can now solve banking problems.
1:17:36
solve banking problems.
1:17:36
solve banking problems. So answer is yes and no. They don't
1:17:39
So answer is yes and no. They don't
1:17:39
So answer is yes and no. They don't really expect to take a participate in
1:17:41
really expect to take a participate in
1:17:41
really expect to take a participate in hackathons but if you have done it it's
1:17:43
hackathons but if you have done it it's
1:17:43
hackathons but if you have done it it's a good thing right if you go you can
1:17:46
a good thing right if you go you can
1:17:46
a good thing right if you go you can show them the project um they really
1:17:48
show them the project um they really
1:17:48
show them the project um they really love that but this model will grow more
1:17:51
love that but this model will grow more
1:17:51
love that but this model will grow more where they want to see your
1:17:55
where they want to see your
1:17:55
where they want to see your work rather than resume right is fine
1:17:57
work rather than resume right is fine
1:17:57
work rather than resume right is fine regime tells you what you've done end of
1:17:59
regime tells you what you've done end of
1:17:59
regime tells you what you've done end of the day they want to see what have you
1:18:13
All right, that's
1:18:16
All right, that's
1:18:16
All right, that's okay, guys. Anything else? I mean, we
1:18:18
okay, guys. Anything else? I mean, we
1:18:18
okay, guys. Anything else? I mean, we have more questions. We're good.
1:18:26
I think we are good, guys. Appreciate
1:18:28
I think we are good, guys. Appreciate
1:18:28
I think we are good, guys. Appreciate it. Thank you everybody. I hope uh I
1:18:31
it. Thank you everybody. I hope uh I
1:18:31
it. Thank you everybody. I hope uh I hope you you guys learned something
1:18:32
hope you you guys learned something
1:18:32
hope you you guys learned something today. I would love to do this again in
1:18:35
today. I would love to do this again in
1:18:35
today. I would love to do this again in next 3 4 months. I always like to you
1:18:38
next 3 4 months. I always like to you
1:18:38
next 3 4 months. I always like to you know share and talk to students.
1:18:41
know share and talk to students.
1:18:41
know share and talk to students. Everybody check out those these new
1:18:45
Everybody check out those these new
1:18:45
Everybody check out those these new skills if you have not done this
1:18:47
skills if you have not done this
1:18:47
skills if you have not done this already. And um definitely definitely
1:18:50
already. And um definitely definitely
1:18:50
already. And um definitely definitely join C# Corner. Not just join you just
1:18:53
join C# Corner. Not just join you just
1:18:53
join C# Corner. Not just join you just go spend time there every week at least.
1:18:56
go spend time there every week at least.
1:18:56
go spend time there every week at least. go for an hour or two slowly learn newer
1:18:59
go for an hour or two slowly learn newer
1:18:59
go for an hour or two slowly learn newer things there because more you learn more
1:19:02
things there because more you learn more
1:19:02
things there because more you learn more words you learn.
1:19:05
words you learn.
1:19:05
words you learn. Um more it opens up your your
1:19:09
Um more it opens up your your
1:19:09
Um more it opens up your your creativity, your ideas, your thought
1:19:11
creativity, your ideas, your thought
1:19:11
creativity, your ideas, your thought process and you know a lot of experts
1:19:14
process and you know a lot of experts
1:19:14
process and you know a lot of experts says some wise person says it that you
1:19:17
says some wise person says it that you
1:19:17
says some wise person says it that you are what your five friends are right. So
1:19:19
are what your five friends are right. So
1:19:19
are what your five friends are right. So if your whatever your five friends are
1:19:21
if your whatever your five friends are
1:19:21
if your whatever your five friends are you will become the same as your
1:19:23
you will become the same as your
1:19:23
you will become the same as your friends. So same thing is you will
1:19:25
friends. So same thing is you will
1:19:26
friends. So same thing is you will become where you hang out. So if you
1:19:28
become where you hang out. So if you
1:19:28
become where you hang out. So if you hang out on C# corner with these guys
1:19:31
hang out on C# corner with these guys
1:19:31
hang out on C# corner with these guys who are every day talking about AI,
1:19:33
who are every day talking about AI,
1:19:33
who are every day talking about AI, learning newer things, you will become
1:19:36
learning newer things, you will become
1:19:36
learning newer things, you will become one of them, right? That's how you
1:19:37
one of them, right? That's how you
1:19:38
one of them, right? That's how you become better. It depends on where you
1:19:39
become better. It depends on where you
1:19:40
become better. It depends on where you spend your time. With that said, good
1:19:43
spend your time. With that said, good
1:19:43
spend your time. With that said, good luck to everybody and um hope hopefully
1:19:46
luck to everybody and um hope hopefully
1:19:46
luck to everybody and um hope hopefully you guys enjoyed and have a nice day.
1:19:51
you guys enjoyed and have a nice day.
1:19:51
you guys enjoyed and have a nice day. [Music]
1:19:53
[Music]
1:19:53
[Music] Do it. Do it.
1:19:55
Do it. Do it.
1:19:55
Do it. Do it. [Music]
1:19:57
[Music]
1:19:57
[Music] [Applause]
1:20:00
[Applause]
1:20:00
[Applause] [Music]