Welcome! Congratulations on your acceptance. We hope you are really excited. We want you to get ready for the bootcamp and have a smooth experience. This means there is some work to be done before the start of the bootcamp.
As a first step, please create at account at our Discourse site. This is a forum that we will use throughout the bootcamp, where we will get to know each other, share materials, ask and answer questions and discuss.
Throughout the prework process, you will install some packages we will use, learn about the command line tools, get used to Emacs, go through a Python tutorial, and refresh your statistics background. The time estimates for each step are there to give you a general idea. Depending on what you are familiar with and what is new, you may spend less or more at each step.
As the final step, you will work on some exercises that go along with the statistics refresher. Since they are all python based, they will allow you to both train and assess your python and statistics skills. There are 6 required exercises. You can submit the answers to these through email, the details are in the relevant part below.
Feel free to contact us if you have any questions. Please do so through the pre-work support thread on Discourse.
You will first follow the online tutorials for installing some critical packages that will be used in the course: command line tools, ipython notebook, numpy, scipy, matplotlib, scikit-learn, pandas and git. You can follow our installation guide to do that.
Please follow and complete the free online Command Line Crash Course tutorial. This is a great, quick tutorial. Each "chapter" focuses on a command. Type the commands you see in the Do This section, and read the You Learned This section. Move on to the next chapter. You should be able to go through these in a couple of hours. Make a cheat sheet for yourself: a list of these commands and (very briefly) what they do.
While we will also use ipython notebooks and the Python IDE during the bootcamp, in the end the process of coding mostly involves writing code files in a text editor and running these files with Python. You can find out about text editors here.
We will work with Python (2.7) throughout the course, and learning and getting familiar with Python is crucial.
Time to freshen up your statistics knowledge! We have a guide for doing exactly that. The exercises go hand in hand with these, so please check both of them.
The 6 required and 6 optional problems are listed here. Try to do them while you're reading the relevant statistics chapters. It would be ideal if you could submit the answers before the first day of bootcamp. However, if you could not finish in time, you can submit them by the end of the first week. Thank you very much.