쉐도잉 연습: How I Would Learn Python FAST (if I could start over) - YouTube로 영어 말하기 배우기

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I taught myself Python at the age of 32 and my dear god I was humbled.
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I taught myself Python at the age of 32 and my dear god I was humbled.
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I struggled with it so much I'd never been a problem solver
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or like learnt to code before and I just really just I struggled with the logic side,
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but I was just learning it the wrong way.
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So this video is everything I wish I knew when I started learning Python.
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This is the only Python video you need to watch.
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Like if you implement what I'm gonna tell you in this video You will learn it
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and at the end of it I want to encourage you guys to build your own stuff your own apps
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So I'm gonna share a project you can get stuck into one of the big goals of my page is
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that you don't just learn but you learn to build your own products.
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So whilst you're learning you can actually make something which the worst case scenario looks good on your portfolio,
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best case scenario becomes a business.
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So let's get stuck in.
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If you're new here, my name is Andrew.
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I got into tech in my 30s.
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I make content around tech,
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code and traveling the world as a digital nomad making apps.
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So if that sounds like your kind of vibe, subscribe if you want.
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Okay first, why should you learn Python?
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Let me motivate you and set the scene.
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A lot of people are saying that you don't need to learn to code anymore because you can just vibe code apps.
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There is a degree of truth in that,
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but people who can code will just make way better apps.
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But for AI and machine learning,
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which is driving all this change in the world,
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Python is like the gateway into this industry.
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It's the fastest growing sector in the world.
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And if you want any technical job in this industry,
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then you need to know Python.
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So maybe you're watching this and you want to change your life.
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Years ago, I was in the same boat.
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I didn't know then, but learning JavaScript and Python really did completely change my life.
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And if you want to work,
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maybe you just want to learn Python or like build apps,
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or you want to work in AI machine learning,
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this skill is going to take a lot of effort.
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You're consistent.
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It will change your life.
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And one thing to consider here is that you don't learn Python in like six months.
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This is like something that you'll be learning for the rest of your career.
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Also, you're not just learning Python.
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Like Python is a language.
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It's the technique.
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The big thing you're learning,
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the big concept, which is going to bring you so much reward in your career,
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is problem solving.
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So what do I mean by this?
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You want to become the kind of person who goes into any job,
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any project, and you can help them with Docker.
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You can help them with back-end work, maybe some machine learning.
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And just knowing Python won't really help you too much,
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but if you're a problem solver and you can work with different technologies,
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this really is what companies want.
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A big part of this video is to teach you how to become a problem solver
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and at the end of the video I'm gonna share the one thing which really helped me in this sense.
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And at this stage one thing I wish I'd done earlier
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was to learn about the context of where my Python code is sitting in the software lifecycle.
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For example if you're a AI machine learning engineer you want to learn you obviously train in models.
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You want to learn where your model fits big picture wise for that product.
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So you want to learn about AI engineering.
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So what's going to happen with that model?
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Or you're making backends in Flask or FastAPI.
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Then you want to learn a bit about the cloud.
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You want to learn about containerization.
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You want to learn about backend and frontend.
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So it'll just help you to have a context of where your Python code sits.
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And you don't have to go too deep.
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Just have a high level understanding of where your Python code fits in,
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spend a couple of days,
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maybe like a week on this.
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And the way I recommend to learn Python and what I wish I did is to pick only one long form resource,
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a big course that's going to teach you all the fundamentals,
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all the basics, the theory,
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all the syntax of Python.
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Just choose one, go through it thoroughly and that's all you need.
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All right and I've handpicked four courses.
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You only need to choose one.
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So two or three video ones,
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One's a paid one and one's a free ebook as well.
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So first one, CS50 from Harvard, super famous.
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This is the best free introduction to Python course on the internet.
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Next one, BroCode.
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Bit of a more of an informal YouTube video you can watch, like 10 hours.
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If you want a book,
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check out Automate the Boring Stuff with Python.
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You have to pay for the physical book,
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but there's a free ebook and you just go through each chapter and there's projects in it.
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Or what I recommend is a paid course from zero to mastery.
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It's like 30 or 40 hours.
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I wanted a longer tutorial.
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It's got really good projects in it It teaches you a bit about AI machine learning as well
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and I just like the learning style so zero to master I can't remember the name of the course,
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but I'll link it in the description Okay,
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at this stage you might be feeling a bit uncomfortable You might have learned a lot of syntax
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And then you have to build your own project
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and you're sat there looking at the screen
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And you're just like how do I solve this and then you feel it's just that uneasy feeling you feel uncomfortable,
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you reach for your phone,
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you go to distract yourself, don't do that.
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Set a Pomodoro timer and sit with it.
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Feel uncomfortable.
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Then you want to logically break down the problem or the project, whatever it is.
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But that feeling you get where you feel uncomfortable and you want to distract yourself with your phone maybe,
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don't do it, lean into it and then you slowly learn to feel more comfortable with becoming a problem solver.
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I've not heard any other youtubers or like programming instructors talk about this,
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this deeper level of problem solving.
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So if you're getting value from this video,
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all I ask, I'd massively appreciate it if you just like the video.
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It'll help me out a ton and subscribe if you like.
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Now a very good question you might have at this point is what about AI
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when all the answers are just there on
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that little chatbot why don't I just ask it these questions and gives me the perfect answers.
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How I use AI and how you should use AI is like your personalized tutor.
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What you don't want it to do is to do the problem-solving for yourself.
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So you've got to use your own initiative here.
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If you feel like you're outsourcing your brain,
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outsourcing your thinking, outsourcing the problem-solving,
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then you're doing it wrong.
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But you want to use it to your advantage like a tailored tutor that you're paying to help you learn Python.
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So ask it specific questions about decorators, about loops, functions, whatever.
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Just ask it specific questions but don't let it do the work for you.
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You should feel uncomfortable.
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If you're not feeling uncomfortable,
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if you don't feel like your brain is hurting,
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it like aches because you're pushing your mind to its limit,
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then you're not doing it right.
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Okay, once you've done half of the course I want you to stop.
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So halfway through you'll have learned all the fundamentals and the syntax of Python like variables,
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loops, conditionals, really basic stuff.
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And what you want to do is go on a website,
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it's completely free, called Practice Python.
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If we look at it Now it's got 40 beginner Python exercises.
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And this is just really basic stuff,
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but you're going to be learning how to write Python code.
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And it slowly gets more complex.
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It's got these little chilies.
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The more there are, the harder it is.
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But this is just a great website I found just to get into the practice of writing actual Python.
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Now at this stage, there might be some concepts like functions or decorators that you're just struggling to visualize.
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There is a great free website for this.
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It's called Python Tutor.
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How it works is it just visualizes code execution in Python.
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So you can write whatever you want in here.
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I can put any function and it will just visualize it for me.
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At this stage in your development, this is crucial.
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So another great free resource I recommend.
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And obviously, if you have specific questions,
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if there's something that's not clicking, ask AI.
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Okay, at the start of the video,
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I said there's one technique which helped me become a problem solver.
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This is it.
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So we're continuing to go through the course that we chose.
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But at the start of every single session,
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we're going to go to a website,
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it's totally free, called Code Wars.
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What this is, is like going to the gym for coders.
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So every single session you sit down to do this course,
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you start it by doing a toy problem.
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This is like a small compartmentalized problem.
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The whole idea of it is like going to the gym and it's going to teach you problem solving.
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So you're given these isolated problems,
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start at the easiest one.
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If you go on code wars,
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it's all based on a CATA system.
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So start at eight and just start solving these code war problems.
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Now, once you graduate, you'll do something called leak code.
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But for that, you usually need to know data structures and algorithms.
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We're not getting into that yet,
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but code wars is a great way to practice this logical thinking and this problem solving.
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Okay, final step.
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So, but first let's recap on what we've done so far.
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So we started off with the right mindset.
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We talked about the context of Python within a project.
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We chose a course.
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Whilst we were doing the course,
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we were doing these toy problems and visualizing the code.
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Now we're going to put everything into practice and start doing projects.
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And there is a GitHub repo called 30 Days of Python.
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The reason I like it is basically 30 projects,
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but each day it adds on the complexity.
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So you start on day one and it's just like an introduction showing you how to install Python.
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It builds up to strings,
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sets, loops, so the basic stuff.
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And at the end of it,
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real stuff you're going to use on the job.
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So, you know, like web scraping,
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Python with a real database like MongoDB.
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And it takes you through the final step,
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which is building an API.
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So this is stuff that you'll use on a real job.
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So the next step now,
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go through each of these projects.
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Now, if you follow the steps I've given you,
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you know the basics of Python and in theory, you're job ready.
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But at the start of the video,
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I said, the big goal of my page is to encourage you guys to learn
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but also build your own products you're trying to sell at the same time.
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So you can continue with AI machine learning if you want or whichever direction you want to go in with.
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I recommend you try and make your own SaaS.
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I've got different videos on my page about how to come up with an idea,
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so watch those.
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I found a really good tutorial which will help you build a SaaS with Python.
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It'll teach you Stripe, Postgres as a database,
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Tailwind for styling and GitHub Actions.
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So think of an idea and if you're up for it,
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try and build your own product.
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Worst case scenario, it looks really good in your portfolio compared to like a generic project.
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Best case scenario, you charge $50 a month,
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you got a few people,
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it becomes a side hustle or like an income for you.
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And that is it.
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And one thing I wanna say is that if you follow these steps,
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I know it doesn't feel like it now,
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but you will learn this stuff.
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And don't forget to enjoy the process.
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Like I look back, I was so focused on where I wanted to be.
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I wish I enjoyed the process more.
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So yeah, if you like this content,
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if you got any value from it, massively appreciate it.
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If you like the video, subscribe if you want.
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I'll see you in the next one.
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Happy coding.
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Ciao.

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이 영상은 파이썬을 빠르게 배우고자 하는 사람들에게 중요한 팁을 제공합니다. 특히, 실력 향상을 원하는 영어 학습자에게는 효과적인 영어 발음 교정의 기회가 됩니다. 힘들었던 경험이나 진정한 동기부여를 통해, 학습자는 투자한 시간과 노력을 통해 진정으로 원하는 목표에 도달할 수 있습니다. 이와 같은 개인적인 이야기를 듣는 것은 말하기 연습을 위한 실제적인 맥락을 제공해 줍니다. 자신을 표현하고, 영어로 생각을 정리하는 데 많은 도움이 될 것입니다.

문맥 속의 문법 및 표현

  • "I taught myself Python at the age of 32": 자신에 대한 경험을 이야기할 때는 과거 시제를 사용하는 것이 일반적입니다. 이를 통해 학습자는 나의 경험을 공유하는 법을 배울 수 있습니다.
  • "If you want any technical job in this industry, then you need to know Python": 여기서 가정법을 사용하여 조건과 결과를 연결하는 구조를 볼 수 있습니다. 이는 영어 문장을 조금 더 복잡하게 만들고, 다양한 상황에 적용할 수 있는 좋은 예입니다.
  • "You will learn it and at the end of it, I want to encourage you guys to build your own stuff": 'and'와 함께 사용되는 문장은 두 가지 아이디어를 연결하는 데 도움이 됩니다. 이러한 구조는 이야기의 흐름을 원활하게 해줍니다.

일반적인 발음 함정

영상에서 'Python', 'project', 'apps'와 같은 단어들은 발음할 때 주의가 필요합니다. 특히, 'Python'은 '파이썬'이 아닌 '파이던'처럼 발음될 수 있어 영국식 발음과 미국식 발음 간의 차이를 잘 인지해야 합니다. 따라서 이러한 단어들을 반복해서 연습하고, shadowing 기법을 활용하여 반복 청취 후 따라 말하는 연습이 중요합니다. IELTS 스피킹에서도 이러한 발음의 정확성이 중요한데, 직접 발음해보며 교정할 수 있는 shadow speak 기법은 아주 유용합니다. 흔히 맞닥뜨리는 발음 함정은 정확한 억양과 발음으로 극복할 수 있습니다.

쉐도잉이란? 영어 실력을 빠르게 키우는 과학적 방법

쉐도잉(Shadowing)은 원래 전문 통역사 훈련을 위해 개발된 언어 학습 기법으로, 다언어 학자인 Dr. Alexander Arguelles에 의해 대중화된 방법입니다. 핵심 원리는 간단하지만 매우 강력합니다: 원어민의 영어를 들으면서 1~2초의 짧은 지연으로 즉시 소리 내어 따라 말하는 것——마치 '그림자(shadow)'처럼 화자를 따라가는 것입니다. 문법 공부나 수동적인 청취와 달리, 쉐도잉은 뇌와 입 근육이 동시에 실시간으로 영어를 처리하고 재현하도록 훈련합니다. 연구에 따르면 이 방법은 발음 정확도, 억양, 리듬, 연음, 청취력, 말하기 유창성을 크게 향상시킵니다. IELTS 스피킹 준비와 자연스러운 영어 소통을 원하는 분들에게 특히 효과적입니다.

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