Boost your career with this online programme brought to you by the Data Science Institute at Imperial College London and Le Wagon Coding Bootcamp.

<aside> โ„น๏ธ This preparation work must be completed in full before the first day of the course. Resources in this document are all available online and free to use (but require registration).



Python is the most popular language of Data Science and will be the one taught throughout the course. Libraries like numpy, pandas, scikit-learn, keras are all written for Python. The course will dive into those libraries from the first day, thatโ€™s why this preparation work is very important to get the basics right.

Before you begin working on some code by yourself, take some time to read the following resources from the official Python 3 documentation and watch the following lecture:


๐Ÿ‘‰ CS50 Lecture - Python (1h48 on Youtube)

๐Ÿ‘‰ A great cheat sheet on Python

To practise some Python without installing anything on your laptop (that is something we will do on the first day of the course), you can use Open a new tab and go to - type print("Hello world")in the text editor (in the middle) then click the run button. Thatโ€™s it! You have a full environment to run Python code in your browser.

๐Ÿ‘‰ Automate the Boring Stuff with Python: This is a great course to start learning Python.Go from Chapter 0 (Introduction) to Chapter 11 (Debugging). You can read the material and you can also follow along the Youtube videos with this playlist. Use to replicate what you see on screen and do some coding yourself as well!

After this course, you should be more comfortable with the basics of programming: types & variables, conditions, loops, functions, composite data structures (list and dict). Python allows you to do Object Oriented Programming as well and thatโ€™s something to prepare yourself too. Again, donโ€™t hesitate to use

๐Ÿ‘‰ OOP Tutorial

๐Ÿ‘‰ CS50 - OOP and AI

๐Ÿ‘‰ Python OOP for Beginners

๐Ÿ‘‰ APIs basics (only first part - free of charge)

After some training on pure Python as a programming language, you can dive into Pandas:

Introduction to Data Analysis (1h18 on Youtube). You can replicate the code by launching a Notebook in your browser.

Once youโ€™ve done that you can treat yourself by watching a 1-hour intro to ML by thoughbot (and if you speak French you can also watch this one ๐Ÿ‡ซ๐Ÿ‡ท)