Bootcamp

This repository contains prerequisites for the python and R warmups, information on the course, and additional resources to go further.

This repository is a work in progress. If you cloned it, get the updates on a regular basis_

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python

The course is an initiation to data structures and algorithms with numpy, pandas and scikit-learn, and will cover the following topics:

  - Intermediate data structures and algorithms
  - Understanding numpy arrays
  - Exploratory data analysis and visualisation with pandas
  - Initiation to data science

• If you're a complete beginner in python, please make sure you have reviewed the 1-learning-path-python chapter and that you have at least covered 1.2-prerequisites by yourself, and done the associated exercises before going to class.

• To prepare for the class, you can read and exercise with Python Data Science Handbook, cloning the repository or exercising with the online version of the book

• If you're experienced in python, and already familiar with the three libraries used during the bootcamp(1.3-data-specifics), you can try to implement one of the projects. The projects are not mandatory, they will be discussed at the end of the class with students who implemented them.

R

• Prerequisites for the R warmup is a basic knowledge of programming that has been covered in the python warmup
• Syllabus: 2-learning-path-R