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Learn to code with Python

What will you be learning?

An insight into the course

There are many excellent resources available on the Internet that can be used to learn to code with Python through self-study. Here I suggest how to use some of these resources – in combination with some materials that I have developed myself – to learn how to write and evaluate basic scripts with relevance to data analytics in the Python programming language.


In about six weeks you will not only learn the basics of Python, but also of two libraries (NumPy and pandas) that are part of the Python ecosystem and that are widely used for data analytics purposes. We start from scratch, so no prior experience with programming (in Python or in any other programming language) is expected.


For the first four weeks, the main materials that I suggest you study consist of ten chapters of a textbook, and all content discussed during a series of web lectures by the author of this textbook (Charles R. Severance) that are available via YouTube. The textbook is:


And the web lectures by Charles R. Severance can be found at the following site:, and should be watched until 5:54:55.


For the last two weeks, I suggest you study the materials about the NumPy and pandas libraries that have been developed for this site.

For all weeks, I suggest you first study the literature/materials mentioned in the table below and then make the weekly exercises that I have developed. In order to test your understanding of the materials, you can then go to another part of this website (‘Test your Python coding skills’) where you will find multiple choice (MC) questions about, and programming tasks for, the materials of each week.


The suggested structure based on a six weeks period:

In order to learn to code with Python, I strongly recommend you to do so using Jupyter Notebook, which can (among others) be done using the Anaconda platform (for more information, see

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Access the Weekly Materials

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