1 Welcome!

In the first few chapters you will be introduced to the basics of the R and Python tracks respectively and you will find helpful explanations to questions you might have in the beginning of your coding journey. There will be a quick introduction to the Data Science track so that you can get started with the project quickly. So let’s get started with the basics!

In all tracks you will work on your project in small groups of fellow students. This not only helps you get the project done faster, it also helps make your results even better. Our experience shows: The different backgrounds of the members and discussing different opinions and ideas will produce the best results. Besides, it is of course more fun to work on a project together than to code alone!
The groups can consist of a maximum of three members. You can choose your two teammates independently, we won’t interfere with your arrangements. It is important that all group members complete the same level of difficulty (beginner or advanced), since the tasks are different in scope for each level. We explicitly encourage you to collaborate with students from different departments. This not only allows you to get to know people from other departments, but may even give you a whole new perspective on the project and tasks. When submitting it is important to note: for a certificate, each person must submit the project individually. However, this can be identical within your group. You can get more information at our first Coding Meetup on May 20, 2020.

Every semester, we at TechAcademy think hard about a new project that is suited for you to learn data science. This semester, the topic choice was rather straightforward. Covid-19 is the dominating issue for our society at the time of writing this project in March and April 2020. We developed this case study as the crisis was unfolding in real time. So the recency of this topic comes at a small cost to you – the data is changing rapidly and so are the results and conclusions. Not every textbook method works perfectly well on this data set – but that’s how it is in real life. We believe that you will learn a great deal about real life Data Science with this very timely topic. Maybe even more than you would with a polished textbook case study and data set.

This case study and the associated project guide was developed and written entirely from scratch by TechAcademy’s Data Science team. Lukas Jürgensmeier and Lara Zaremba developed the project in R, while Felix Schneider and Manuel Mair am Tinkhof developed it in Python. We thank Jonathan Ratschat for providing valuable feedback on earlier versions of the project.