Programming Skills

Programming and Python

There exists a great variety of programming languages. At Business Data Science, Python is used in several courses and for research work. If you are new to computer programming, keep in mind that learning to program in the first place is significantly more difficult compared to learning a new programming language.

Test your Python skills

Precourse Python test

The test has been created by Jeroen Engelberts, teacher of Parallel Computing and Big Data and updated and tested by Meike Morren, teacher of Natural Language Processing. 

Python resources

For learning Python, several good resources are available on the web.

Code academy offers an introductory course into Python: 

• Code Academy – Learn Python

A similar introductory course is offered by learnpython.org: 

• learnpython.org

A course offered by Google is somewhat more extensive and better suited for those who have some programming experience: 

• Google – Python Class

Learning Python the traditional way by means of an introductory book is of course a viable alternative. The publisher O’Reilly offers very good books on almost every subject related to computer programming. 

• Learning Python by Mark Lutz, 5th edition 
• Introducing Python by Bill Lubanovic, 2nd edition

Statistics and R

Within research environments, the software package R is most often used for statistical modelling and analysis. At Business Data Science, R is used in several courses. It is is available as free software: 

• The R Project for Statistical Computing

Their own introduction to R is quite extensive: 

• CRAN – Introduction to R

DataCamp offers a free introductory course into R: 

• DataCamp – Introduction to R

A more accessible introduction into R is available as an open book: 

• Intro2R.com

Two very detailed books on using R in a business data science context are available: 

• Introduction to R for Quantitative Finance by Gergely Daroci et al. 
• Introduction to R for Quantitative Economics by Vikram Dayal

Overleaf, Github

Many students will share their work and collaborate with each other on Overleaf and Github. We strongly recommend you to familiarize yourself with both.  

Rmarkdown, Google Colab

Some courses involve the presentation of code in pdf files, as well as working with large amounts of data and corresponding heavy processing tasks. To save time during the block we recommend you to also familiarize yourself with Rmarkdown and Google Colab.