Resources

Resources

Introduction

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

Python

  • 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.

Web

  • 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

Books

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

Development Environment