Introduction to Data Science


Today I’ll pass out the syllabus and answer and questions you have about the structure of the course. Then, we will leap right into getting you set up for the semester with GitHub and Python. On Thursday we will spend more time framing the course and what we hope to get out of it more broadly.


If you do not already have an account, go to the main webpage and create a free account. Try to pick a professional name as you may find that you want to make this public at some point:

Next, follow this link and accept the invitation:

Assuming you have a valid GitHub account, this will set up a repository where all of your projects for this semester should be posted.

Create Workspace

Now, either download the entire repository as a zip file or, if you use git, clone the repository. (If GitHub is being a pain, you can also download the zip file directly) Either way, put the results somewhere on your computer that you can easily find and save. You’ll put all of the materials from this class inside that folder.

Setting up Python

Download software

We are going to use a version of Python distributed by Anaconda. This should simplify our installation and streamline our work for the semester. Note that we will be using Python 3.

To start, navigate to the Anaconda website:

You should see a page like this:

Click on the correct platform and download Python 3.6. This is a large file so it may take a few minutes. Note that there will be a pop-up to be on their mailing list. Just ignore this; the download will start automatically.

Once the download is complete install the software on your computer. Note that on macOS you need to drag

Start Anaconda Navigator

Once installed, run the Anaconda Navigator from your applications directory. You should see a screen that looks like this:

If you have this screen, you should see a tile called “jupyter”. Click the launch button below the logo. This runs the Python engine and opens a notebook in your web browser. This is what we will be using this semester to run Python code.

Now, once you save a Jupyter Notebook, navigate to where you saved the file and open it:

Today, you should complete both tutorials 1 and 2. In the future, you can see which tutorials/projects are associated with each class through the matrix on the front page of our class website.


As a final to-do for the first class, I have some written questions that I would like you to fill out. Please hand these in before you leave!