We primarily use Python as the language of choice for Data Science within the programme. As such, we would suggest you first take a look through a resource such as Journey from a Python noob to a Kaggler on Python.

The page below gives various resources recommended by our Staff, Mentors and Students.

Online Courses



  • Programming foundations with Python Udacity #Beginner
  • Introduction to Algorithms Udacity #Intermediate
  • Full stack Foundations Udacity #Intermediate

This should be a good base for you to start our programme. If your programming is shaky or you don’t have experience in Python, it would be best that you start with these classes.


  • Introduction to JavaScript Udacity #Beginner
  • The Django Book (Updated for Django 1.8) DjangoBook (not a class but, great to learn Django) #Intermediate

Data Science

  • Intro to Data Analysis Udacity #Beginner

The courses below are primarily aimed at Phase 2 of the programme (December/January). It depends mainly on what project a student is working on.

  • Practical Machine Learning (from Johns Hopkins University) #Intermediate
  • Cluster Analysis in Data Mining (from Jiawei Han) #Intermediate
  • Text mining and Analytics (University of Illinois at UC) #Intermediate
  • Text Retrieval and Search Engines #Intermediate
  • Data mining (University of Illinois at UC) #Intermediate
  • Data Visualization (University of Illinois at UC) #Intermediate
  • Statistical Inference (from Johns Hopkins University) #Intermediate


These are completely optional, but can be great references for participants to keep for the future.

Development Environment