 In this video, we're going to learn how to install Python on a Windows machine. So first, let's open a web browser and go to a website called anaconda.com. Anaconda is a company that offers various products in the field of data science and also different versions of Python. So under the products tab, there are the different versions and for this course, we are going to use the individual addition also called the open source distribution. So let's click here. On the side of this version, we see the download button we click here. This takes us all the way down to the bottom of the page where we'll find different options to download the so-called anaconda installers. One for each of the major operating systems, so for Windows, Mac OS and Linux. For all of the systems, there is a 64-bit and a 32-bit version. So most modern systems run on 64-bit. Therefore, I'm going to download the 64-bit version for Windows and this download will take about 40 seconds. So we can check here. And in the meantime, we are going in the start menu and click on settings. Go to the system settings, click on the about tab. And then under the where it says system type, we see that our system is indeed a 64-bit system. So this is where you would find the information if it's a 32-bit or a 64-bit operating system. OK, so let's check how our download is going on. So just a few seconds left, download is completed. So let's go to the downloads folder and click on the anaconda installer that starts the installation process. We click on next, we confirm the license agreement. Then in the next option, where we can choose between an installation just for me, that is the current user that is signed on on this Windows machine. Or if you want to install anaconda patent for all users, my recommendation is to just go with just me. This keeps a couple of things easier. We keep the installation path as it is. And then in the next settings, we register anaconda as the default Python version on the system. But we do not add anaconda to the system path. Now the installation starts and this should take roughly two to three minutes. So in the meantime, what I'm going to do is I'm talking about an alternative way to install it. And most importantly, it's actually not the alternative, it's actually the common or the canonical way of installing Python. So let's go to python.org, the official website of the Python Software Foundation. And here under the downloads tab, we click here, we have the option to download Python for different versions, in different versions for different systems, and so on. We see that currently the latest version is Python 3.9. The anaconda version that we downloaded is the Python 3.8 version. Under all circumstances, you have to make sure that you're installing a rather recent version of Python 3. So you should not install anything that is older than 3.7 for this course. And under no circumstances should you ever use Python 2.2.2 is not supported anymore as of last year, actually. So if you start to learn how to code, then you should choose Python 3. So what is the difference between downloading Python from the official website, Python.org, versus from anaconda? So the main difference is that when we install Python from the Python.org website, then that means we only get Python. So basically the pure Python as it is, there's no addition and no add-ons. On the contrary, when we install Python via the anaconda distribution, then we also get many so-called third-party packages automatically installed. And in particular in the field of data science, there are many. Some of them are called NumPy, Pandas, and there are various many more. So because of this beginner course, and I want to keep things simple, I am choosing not to use Python.org version because in that version, I would have to make you download and install many, many third-party packages later on. And in order to prevent that, we use the anaconda version, which already comes with most of the important third-party packages for this course. So let's check how far the installation is. It is almost done. So if you scroll up here in this window, we see all the so-called, so here we see NumPy actually. So here are all the third-party packages that are automatically installed that otherwise wouldn't be there if we install from Python.org. So I guess we have to wait a little bit more and should not take too long now. So this is basically, yeah, we are not going to cut this video because it's not that long. Okay, and then once this is installed, one of the other things that comes with it, maybe I can show you that in the meantime, is the so-called Jupyter project. So Jupyter, spelled with a y, .org, is a project that basically provides you a programming environment. Here it is, here are a couple of screenshots that runs in the web browser and that we are going to use to do the coding for our course here. Okay, so there are many different ways of how you can run Python code, but we are going to use the JupyterLab environment and that is also included in the anaconda version. So now the installation is complete. In the next option, we just skip that, we do not need PyCharm. This is a proprietary and commercial version of a software development environment. And then the tutorials, we uncheck them because I'm going to walk you through the basics. So we won't need that. And now that we are done, we can delete the anaconda installer from the downloads folder. We don't need this anymore. And then we go into the start menu. And here on the left-hand side, we will find the anaconda 3 64-bit folder. We click on that. There are a couple of options and we are going to click on the anaconda navigator option here. Okay, so now we see a couple of black windows popping up. That means there are a couple of programs running in the background. And quite soon, anaconda navigator is going to show up. So here we see the screen logo here. That is the logo that is shown until the anaconda navigator has loaded. So now this is done. So what is anaconda navigator? This is a software that is created by the anaconda company that basically summarizes all of the things regarding Python and programming that has been installed. And we are in the beginning. You are going to use the JupyterLab environment here. For some of you, maybe the Jupyter Notebook version. This is also an application that runs in the web browser. Maybe a good alternative. This is like the old version and JupyterLab is the newer thing, so to say. And so Jupyter Notebook has a couple of less options, but sometimes that is what you want. And then there are a couple of other options. So now let's click on JupyterLab, let's launch it. And now what's going to happen? Because as I said, JupyterLab is an application that's going to run in the web browser. A new tab is going to open. And that is now the JupyterLab application. We see in the URL, it says localhost. Localhost is a special name. That means we are not going on the internet here, but we are keeping things on our machine. And the number, the colon 8888 that we see here, this is the so-called port number. I'm not going to explain to you what that is. You will figure that out yourself. Just notice that 4 times 8 is the default port number. But it could be that you see a different number on your installation when you start Anaconda. This should not be, yeah, there's nothing wrong with it. This can be any number basically. And yeah, that is like the address. And in the background, the web browser then communicates with some software that is running on your machine and that provides you this website basically. Okay, so what do we see here? On the left-hand side, we see folders. These are the folders on my Windows machine here. Here we have the download folder that we just saw. And now the next thing we need to do to work with the materials in the course, we have to download them first. So let's go to another website. That's the official repository for the course materials that are hosted on GitHub. So the website is called github.com slash. And then comes my username, which is web artifacts slash. And then it is intro to Python. And what that does is that takes us to the GitHub repository for this course. And what a GitHub repository is, it's basically like a folder on Dropbox. But it has additional functionality that is very useful when you work with code files. So it's like a Dropbox on steroids. That's usually how I describe GitHub to beginners. And here we see the files, the folders and a couple of files here. When we scroll down, we see a read me file with the installation instructions that we are currently going over. So you could also read up how to install it if you have any troubles. And at the very top, there is a link to a file called contents. And if you click here, this takes us to the contents overview of all the materials. So here are the links to all the files in a just table of contents fashion. But now let's go back here to the main site on GitHub. And to download the materials, the easiest way is to click on the green button here on the top of the page. And simply click on download zip. And this is going to download all the course materials as a zip file. This should be very fast. And then let's open the file folders here. File Explorer, go to the downloads folder and we see a zip file into the Python and so on. Let's right click on it and say extract all. And this will now give you the folder to specify where you want to unpack all the files. So let's do that. This also should not take too much time. And inside the folder, there is another folder and there are all the files in there. So what I'm now going to do is I'm going to cut out all the files and move them one level up. So when you unzip a zip file that has one folder inside that, you get one level of folder too much. So to say, so now I have in the downloads folder a folder called into the Python. If I double click on that, I have all the files here. Okay. And now the zip file, I don't need anymore. So let's also delete that. And this folder, the intro to Python folder, you can basically move anywhere on your file system where you keep files for courses. I also recommend that every once in a while you update them. If you do that via downloading a zip file, you have to do that manually, so to say, by downloading the zip file and the latest version of the zip file and figure out which files have changed. There are different ways of working with GitHub, but they are not necessarily beginner friendly. So that is why we choose the option to download a zip folder. Okay. So let's close the file explorer and go back in our browser into the triple the laptop. Now let's click on the downloads folder here. And here we see the intro to Python folder now double click here. And these are all the materials for this course. Okay. So what we could do now, for example, is we could go into the first folder, zero, zero, intro. This is the first chapter. And then it's click on the file, zero, zero content. And this is going to open the first chapter, the first file in the first chapter of the book. You could now scroll over it and read it. But in a future video, I will show you how you can work with these files in a more effective way. This was just now only to show you how to download them, those files and how to open them. And yeah, so this is how to the lab works. And there will also be another video that will explain to you how you should navigate into the lab. So that is it for this video. You now have seen how you can download an account I installed it on a Windows machine on a Mac system. It will be very similar. And on a Linux system, if you're using a Linux system, I guess you can figure out how to install an account yourself. So we are not going to have a tutorial for that. Okay, so see you in the course.