General programming techniques
Python environment. Data structures: numbers, strings, lists, tuples, dictionaries. Basic language elements: loops, conditions, functions. Modules. Input and Output. Debugging. Machine learning and data mining in Python.
The NumPy package for scientific computing
The pandas data analysis library, including reading and writing of CSV files
The IPython and PyDev development environments
The Seaborn and Matplotlib 2D plotting library(drawing attractive statistical graphics and visualizations)
Language concepts of R: variables, vectors, matrices, data frames
Importing data from text and spreadsheet files.
Using external R packages.