Live Code, Getting Started Getting started with the notebook dashboard The dashboard is the page that is displayed to you right away. The folder from which you began Jupyter Notebook is listed on this page. You can navigate your file system using the dashboard in the same way that you would with any other file explorer interface. It is crucial to remember that the Jupyter notebook server is now executing on this file system. Even another computer could be the server. You will see a different UI if your laptop's server is not set to localhost. At this point, we want to remind you to follow along if you haven't already started doing it. We know one of the biggest obstacles to success in online classes is getting started working with the infrastructure and your learning environment. So we really want you to do this with us. We are just going to get our first notebook started, run some initial code, and add some documentation. It shouldn't take you much time, but it will get you up and running. If you get set up now, for the rest of the course, you'll be able to follow along in notebooks with the material we present and play around with the code yourself. Creating a new notebook Click the "New" button in the dashboard's upper right corner to start a new notebook. Choose "Python 3" as your Python version in this box. Once you have done this, you will be provided with a new notebook. To give it a name, click "Untitled" at the top. We'll call it "Intro Notebook" in this instance. So we gave our notebook a new name. Returning to our dashboard, we can see that a new notebook file with the name "Intro Notebook.ipynb" has been added; this is the new notebook we just created and renamed. In the beginning, there's sometimes some confusion as both the notebook application and the notebook are called notebook, but they are separate. The notebook application is a web application that creates the interface in the browser and executes Python and other languages' code. The notebook file is a file format with the .ipynb extension that saves code, images, and text in a single document, making it easy to share. As we said before, this feature has gained lots of popularity in data science. You presumably already know this, but your browser's "Intro Notebook" notepad is in a different tab. You can have multiple open notebooks open at once. Any new notebook you open will be in a new tab like this. Getting started with coding Now let's get started with coding using the code cells. Hopefully, you're following along, but please feel free to pause the video and try each step we show you if you fall behind. It is normal to take some time in the beginning, so don't worry if it's causing some confusion at times. We will now click on the first cell. Simply click the mouse in the rectangular cell in the notebook and type Python code. For example, you can write print("Hello World!"), which is our traditional greeting in any computer science programming course. This code can therefore be executed in a variety of ways. One method is to select "Run" from the toolbar up top. You should simply obtain the outcome that was written, which is "Hello World," as seen here. Alternatively, you can click and hold that cell.