 OK, so I don't know how much was said about this tool in the previous talk, because my tie is not that good. But I'll say a bit about it. It's a tool that is developed by Google, obviously. Not entirely, though. Not entirely. It's an open source project. It comes from the Jupyter Notebook. I don't know why it's flicking, but yeah. So it's a really good tool. I would say it's not the best tool for beginners, but it can be used for beginners. And it's a good way to get into the field of programming and progressing, because there's a lot of tutorials out there using this tool. This is based on a tool called Jupyter Notebook. Jupyter Notebook, it's similar to this, but it's the actual open source project that you can actually run on your own computer, or you can run it on different servers. Why are we using Collab? Because it's easy for us. I give you the URL. You can just access. We can start working. We don't need anybody to get anything installed or anything. So we just access this, and we start coding. Also going to do some introduction into Python. And then we will start coding and see how this works. So Python, it's also an open source project, of course. This is the Python.org. So it's also an open source project. So if you get good at programming, you can actually collaborate to Python. You can download the actual code from Python. You can add your improvements, or you can help with any of the libraries that are out there. Why learn Python? There's many reasons for learning Python. It's a very good Python for things like rapid prototyping. So even though it's not the most efficient way of doing things in the end, it might not be the most efficient language. It is very efficient when it comes to the time you spend working on it. So if you want to prototype something very quickly, if you want to come up with a test, a solution, see if you can actually get something out of your idea. It's a good way to do it. It's also very, as I said, it's very fast for developing solutions. So there's a lot of people using it. It can be used in a very wide range of areas. So there's libraries on Python for pretty much anything. You can do since web development. So I don't know if you guys heard about Django. That's for web development. You can do AI. There's tons of AI that's done in Python. Keras is one of the main libraries that we actually teach when we're teaching AI in the academy. Why Keras? As I said, it's not the best option maybe for developing an AI for a self-driving car. But it's a good way to get into the field and to get an overview how to do it. And you can get pretty much good results that you can use in certain environments. More things that you can do with Python. You can do robots with Python. You can do desktop applications in Python. You can do lots of things. I think if you click around, I always encourage people to go into the website. It's very important that you actually learn how to do things by yourself. So one of the key things that we always encourage in our courses and workshops is to check out the documentation. So as we go through coding together, the documentation will play a key part. So every time we need something, we come here and we look for the documentation. We can figure out the answer. Why we do this? Because we're not here all the time. So OK, I'm here today and tomorrow. So you can ask me a question. Feel free to do it. But after tomorrow, maybe we don't see each other again. So the best thing that you can get out of one of our workshops or one of our classes is to be self-sufficient. So we prepare everyone to know where to look for information and how to find the people that will answer your questions. So one of the main things, the first main place that you have to use when using any project or any language is their documentation. Because that's where they try to explain how things work. There's also other sources. You can go to Google, try to Google your questions. You might end up, most of the time, on something called Stack Overflow. So I don't know some of the programmers that know that will probably end up there. I end up there pretty much all of the time. Because I'm really bad with the syntax. I tend to forget that every now and then. I just know what I want to do, but I forgot how to do it. So type it on Google, end up on Stack Overflow. It's a website for question answering for programmers. So especially, you'll find yourself there pretty much all the time. So that's that for the Python part. It's a community-driven project, as an open source project, up until recently, was lead by this guy called Widow Van Rosum, which was the founder of this language. He stepped down recently. And now it's just driven by the rest of the community now. And yeah, so let's get a bit into the call-up tool. All right. So if you have any problems, any questions at any time, we have about 10 minutes, if I'm not wrong, right? So on these 10 minutes, we're going to try to mess around with how call-up works. And then probably at four, I'll go in more detail on the Python language. So when you write Python, basically, we write different instructions. And then the Python interpreter will execute those instructions for us. That is how it works. And what we can do in call-up is that we can do that online. And we can just write it using our browser. And this will run in some server on the Google data center. And then we'll get a result. That's how we're going to write everything here. So there's different parts here that you use this. And you probably had to open your Google account, because this basically will save a file into your Google Drive. So this is, as a regular file like any other dog file, it will be a call-up file, which it's called a notebook. So you will find through your learning process, if you keep digging into Python solutions, trying to learn more Python, you will find a lot of notebooks. So these notebooks are very useful for learning, because they have parts of code and parts of explanations. So this tool is widely used for tutorials. That's why we think it's very important for you guys to learn how these tutorials, these notebooks, work. So you can actually learn how to run other people's tutorials. There's a lot of them out there. Here you can see there's the files. The most important part in the end, you can actually just close this. And you can just click on File and create a new Python 3 notebook. One thing that I didn't mention, and it's somehow important in Python. So it's an open source, it projects basically. It evolves in time, and it gets different versions. There's two main versions. There's different versions in Python, but there's two main ones. There's a Python 2 and a Python 3. And something to take into account is that they have big differences between them. So whatever is written in Python 2, it's not usually compatible with whatever is written in Python 3 and all that. So be careful when you're looking, especially when you're looking into the documentation. If you're writing Python 3, which is my recommendation, if you're starting right now, Python 3 is the latest. So just go ahead with Python 3 and try to not even look at Python 2. So you should be on the safe side if you code everything in Python 3. So we teach Python 3 because it's the latest. And I would say there's no reason on actually trying to teach the old one. Let me see if we get the call up. Oh, I need two signing. Let me just open this in one of my tabs. Where's my tabs? Just open this. Wi-Fi's getting slow. OK. So the first thing that we're going to learn, if I manage to load my call up tool, I'll create a new one here. If you guys have any questions at any point, or if you guys run into any problems, feel free to let your hands. And I'll be happy to answer any questions. So the way we do the workshops is basically we open one of these tools. We sit together and we write code altogether. So things to take into account about the call up tool is that we can do two things. We can write text. You can see it up there. I don't know if it's too small for you. But maybe if you guys have it on your own computer, you can see we can write code and text. There's two types of writing that we can do. So we have something called cells. This is a cell. So what we have here is a cell. This little square with a play on the left, that's a cell. So if I go here and click on text, it will create another cell that is text. So there's two types of cells. So cells for text, cells for code. So this one is for text. The previous one is for code. I have two cells. I can go back here. And now I'm editing the first cell, which is code. So here I can write code. And here I can write text on this one down here. If you look at the tools bar that you get there, it looks like a text editor, normal text editor. So this is why these are popular for tutorials. Because when you write text, you can write the explanation. And then when you write code, you can write the code. So that's why we use it very frequently in our workshops. So let's go ahead. And I'm going to remove this one. We can remove delete cell here, for example. And I'm going to just keep the code cell here. And I think we have five minutes. I'm going to write the first line of code. And the first line of code that everyone learns when we learn a language is the hello world. That is the typical one that everyone learns. So let's go ahead and print the hello world. So basically, the way to print in Python is that we do print, print straightforward, open, close, rackets. And then we pass a string here. So we use double quotes. And between the quotes, we can put whatever we want. So we're going to put hello world, right? So now if we want to run this code, we just have to click on the run cell icon here. And if we click, my mouse is not very good. If we click there, Google seems to be a bit slow. We get the result right under, right? So what Google is doing, we say print hello, hello world, and we get hello world, right? Is everyone on the same page? Everyone got the hello world? Yeah, great. Yay, first line of code. Now let's do another one, more code. We click again, right? We can write more code in the next cell. So we can print something else, right? So I can print. Let's not print hello world. Just print something that you just want to print. I'll print hello force H. Then I'll run it. Click on the run. And there you go. We get the second one, right? So we run the code on our cell. So we can also write more than one line in one cell. So we can have, let's put the two prints together. So we can have more than one line in the same cell, right? So here, I'm putting two lines in the same cell. So when I execute this, I'm getting the result of both lines, right? So you can group the code in cells as much as you want, right? That is how Collab works. Now, because we're running out of time, I'm going to show you how to do a text. And we're going to leave it here. If you want to get some more of these Python workshops, we can see each other after the break, right? Let me show you how to do the text. It's pretty straightforward. We can do text here. And then we get a text cell here, right? And then we can just write whatever we want, right? So I'm going to go ahead and write something. So you can see it's just basic text, right? So when you put it here, you can run it. Basically, there's a shortcut to run it that I use. So if you do Shift, Enter, it will run the shell. But if you click on some other, it will just keep the text there, right? You can format the text. You can make it nicer, make it a title. So this is the actual view. On the right, you get the actual view of how it will look. And this is the markup language where you can just obviate for now. You just use the bar on the top, and it should be fine. So this is how it will look. So if you see, I created a title. So I click on the title button. So now, if I click somewhere else, you see that my text looks like a title, right? So I got my text looking as a title. And then I can keep writing code here, right? So because it's already 3.30, we're going to stop right here. Anyone has any questions about the coding, about the call up? Feel free to ask me now or later. And then, if you guys want to learn a bit more, I'll see you after the coffee break. I think it's on X02, if I'm not wrong. But check the schedule, because I might be, all right? Thank you very much. We're using this because not everyone has Python installed in their computers. So it's much faster if we go into the online tool. And another reason is I usually, because as I said, there's a lot of tutorials that come in this form. In Colab Google, I think you can do, it's mainly Python. But I think you can do, I don't know how. I think it's mainly Python. I would say in Colab, it's mainly Python. If you click on File, right? Let's see. You can basically create Python. Yeah. So you can, I don't know about the Jupyter Notebook, which is the tool that is used by, because I think I know they have some efforts into building some other kernels for other languages. But initially, it's Python. Yeah. But there's other online tools that you can use for other languages. We choose this one because it's actually pretty new. We think it's going to have a long-term life. It's very used. Especially in the fields like data science and artificial intelligence, and for teaching and tutorials. So yeah, that's the main reason we use this one. And to avoid problems with installations and different configurations in computers and all that. Yeah, just speed up everything. Yeah, well, for learning, it's a good thing, right? Then you can try to figure out how to install it and all that, which is different for every computer. You might have Windows, or I don't know. This depends. All right. OK, guys. So enjoy your coffee, and see you later.