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So in this lecture, I want to give you a brief rundown of how to use GitHub along with several extra

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coding tips.

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Now, if you've never used GitHub before, then there are several ways for you to download the course

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repository.

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There are also several ways you should not download the repository.

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So first, let's start with some options for what you should do.

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Option number one is to use the Git clone command.

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You can enter this in the console as you can see here.

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Option number two is if you are not comfortable using the console, then you can simply use the download

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button, although I would still prefer option number one.

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Now, one thing to keep in mind is that the Internet is a constantly changing place, so do not freak

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out if GitHub has a new design by the time you visit this page.

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I am confident in your ability to figure this out.

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And the reason I mention this is because I had one student in the past who looked at this lecture and

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saw that the buttons were a different color or a different shape or something, and then all of a sudden

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he didn't know what to do and couldn't follow the lecture.

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But really, it's not that hard.

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All you need to do is use your pattern recognition abilities.

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So consider this your first exercise for the course.

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By the end of this lecture, you should have the entire course repository downloaded to your local machine

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using either of the two methods above.

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Now please note that if you're new to get or GitHub and you find yourself a bit intimidated, please

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do not be.

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You do not have to know how to use git for either of the previous two methods.

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Now, here are some things you should not do that I've seen several students do in the past.

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Number one, do not try to download each file one by one.

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As mentioned previously, this is not the way to use git.

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Number two.

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On a similar note, do not go to file and save as this is not how to download files from GitHub.

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Doing this will download the web page to view the file, not the file itself.

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So if you look at the file and you see a bunch of HTML, you know that you did it wrong because there's

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no HTML in this course repo.

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In fact, number one and number two are very silly because they actually take a lot more effort than

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simply using either of the methods I mentioned earlier.

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So it's actually more difficult to do this the wrong way than to do it the right way.

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And number three, if you want to fork my repository, please feel free to do so.

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But try your best to keep it up to date.

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I make updates constantly, so make sure you pull these updates and if you don't think you'll be able

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to do so, then simply use the Git clone command instead.

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And on that note, when you do download my repository, make sure it's actually my URL and not someone

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else's fork.

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And number four.

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So this might sound silly, but your fellow students have proven to me that this needs to be said.

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There is no need to type anything character by character.

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Simply use the copy button.

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So if you come back here and you say, I can't type all these characters, it's too complicated.

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I'm going to refer you back to this lecture.

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So one extra note about the GitHub repo.

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Most courses also contain a file called Extra Reading text.

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This file contains reference material for the course like journal articles, books and so forth.

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So if you hear me referring to extra reading text in the lectures, this is where it can be found.

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Reading these materials is optional, but they are there in case you want to further your studies.

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So I want to mention a couple of points pertaining to the code in this course.

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Firstly, some of you, especially those who don't necessarily meet the prerequisites, may be asking

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what is get and how do I use it?

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The short answer is Git is a way for developers to manage and track changes in their code.

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You might be used to writing code by yourself, but when you're working with a team of two or ten or

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even 10,000 people, you need a system to keep things in order.

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So this is why, for example, Git is superior to uploading code files to this website and learning

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how to use Git is very simple.

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There are many tutorials out there that will work just fine for this course.

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You only need one command, which is the one I showed you before, so you don't even need to understand

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yet.

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You just need to copy and paste the command I gave you.

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And therefore I don't suspect this will be an issue unless you also don't know how to run commands.

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But if that is the case, then as mentioned, you can simply click the button that says download.

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At this point, I'll assume you need no further assistance.

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And just as a side note, although you don't need to know how to use Git for this course, it is a valuable

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skill that will be necessary if you plan to work for any company where your job is to write code.

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I don't know any companies that write software that do not use some kind of version control I get.

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So if you do want to have a job in this field, that's something you're going to have to learn about

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sooner or later.

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Now, another common question I see from beginners is should you code along?

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The short answer is no.

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Now, you may have taken online courses in the past that encouraged you to code along.

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But the reality is this is going to give you a very false impression of how code is actually written.

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Coding is not a monkey see monkey do type of thing.

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If you're learning to play guitar or do some yoga moves, then yes, that makes sense.

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But coding involves lots of thinking and not just typing.

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If you think you're going to write a complex algorithm in 20 minutes without actually paying attention

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to design or structure and without debugging and going back to fix things, think again.

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Real code in the real world is not written linearly from start to end.

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If you've gotten this false impression from other courses, now is the time to improve your approach.

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I encourage you to watch the lecture, should you call it along for a more detailed discussion?

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This brings us to our next point, which is what are the exercises for this course?

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Now, in some cases this will be obvious because I'm going to say, here is an exercise.

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Please do it.

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But sometimes it's going to be less obvious and I'm going to trust that you've watched this lecture

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and understood what I'm saying.

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Basically, any time that you see code that is an exercise, there are two types of code you might see.

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Number one, I've just taught you an algorithm, in which case the next code lecture will involve an

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implementation of that algorithm.

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And number two, I'm going to walk you through how to use a library or an API, for example, TensorFlow

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or PyTorch or stats models.

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So what is your exercise?

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Well, for case number one, your exercise is to implement that algorithm yourself before you ever see

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my code.

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My code is actually the solution to that exercise.

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So don't take what I call the couch potato approach where you just sit there watching each lecture one

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by one without doing any coding.

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That is not the intent of this course.

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And if you're looking at the solution to the exercise before you do the exercise, this is basically

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cheating and copying your homework.

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Now, obviously what you do is up to you, but I hope that you'll do the exercises as intended.

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Now for case number two, it's a little bit different.

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Obviously, you're not going to know the syntax for a library or an API.

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Before I even show it to you in this case, you should go ahead and watch the full code lecture, which

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will show you the syntax and how things work.

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Replicating the code is very useful because you're building muscle memory and although this sounds like

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it should be easy, it's not.

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In fact, making mistakes when trying to replicate the code is the number one mistake I see on the Q&A.

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And yes, you heard that correctly.

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Even after seeing all the code work perfectly right in front of their eyes, students still have trouble

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just copying that code without making mistakes.

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And for those of you not typing code at all, a lot of people mistakenly believe that just seeing the

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code is enough, but actually being able to type the code makes you much more capable of using it in

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the future.

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But the most important exercise comes after you've watched the lecture.

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You should be able to implement that same code yourself on another data set you care about.

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I assume that you're taking this course because you have some data sets you want to analyze, and if

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not, there are plenty of resources out there where you can find free data sets.

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So please choose one that interests you.

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Note that by this measure, most of my courses have at least 10 to 30 exercises, so try to do as many

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as possible.

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And also note that many courses contain examples of both number one and number two types of exercises,

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and you should be able to recognize it when you see it.

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So hopefully the exercises for this course are clear, and if not, please make a question on the Q&A.

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Now, the next question I want to tackle is a funny one, because I honestly didn't think that this

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was a question I would need to answer.

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But here we are.

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So some students really like Jupyter Notebook very much, while other students dislike it.

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Some students really like Pi charm.

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So you might ask, why am I not using whatever your favorite tool is?

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And the answer is this question is totally irrelevant.

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Now, you might think I'm being dismissive of your concerns, but in fact, the reason people have this

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question is because they don't yet know how Python works.

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After this lecture, I hope you'll have a better understanding.

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So in this course I'm providing you with Python code, you'll get that Python code either in a code

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lab notebook or a python file, but there's really no difference.

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Remember that in this course, this is a video course you're just seeing code on a screen.

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What I use is irrelevant because you can't touch it nor interact with it.

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I may as well be using Microsoft Word or PowerPoint and it would make no difference.

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What you do with that Python code is totally up to you.

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You can take my Python script and paste that into a Jupyter notebook or PI charm or open it up in Visual

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Studio code.

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It's completely your choice.

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Python code works the same no matter what environment it's in.

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The same code will work in a python file in Jupyter notebook, in code lab, notebook and so forth.

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And if you're having trouble understanding this, please use the Q&A so I can help you sort it out.