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.
- 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.
- The Django Book (Updated for Django 1.8) DjangoBook (not a class but, great to learn Django) #Intermediate
- 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.
- We use Ubuntu
- We use Anaconda Python Distribution (Python 2.7)
- Learn Git + Gitlab
- IDE of choice Pycharm