Learning Python

A collection of useful and free (or very cheap) python courses

Melchor Sanchez-Martinez
18 June 2021


As a course instructor of python, when the course arrives to the end is usual that some students ask me about extra resources to further develop their skills in python, if possible in relation with bioinformatics. That’s logic as I teach python for bioinformatics (beginner/entry level).

As the question is recurrent I have collected some reference during the last years that I found interesting and useful. I have categorized them as purely python , bionformatics & genomics and a mix of python and bionformatics & genomics as well as other related resources. These courses are free or almost free. With almost free I mean courses from Udemy that regularly have discounts and can be get for 10-15$ or even some Coursera specialization that can be get for around 50$.

Python and Bioinformatics Learning courses

Purely python

Udemy Python bootcamp

Udemy Python Programming tutorial

Software Carpentry

Kaggle Python tutorial

Bionformatics & Genomics

Coursera bioinformatics

Coursera genomics

Coursera Dna sequencing

BIOL311. This one is in spanish.

Python + Bionformatics & Genomics + Related resources

Harvard informatics. Here there is a collection of diverse bioinformatics resources, related to python, statistics or RNA-seq among others.

Sebastian Schmeier collection. Here Sebastian Schmeier has created its own collection of courses covering computation/biology/bioinformatics in general. Inside the list there are links to python and bioinformatics resources but also to related topics.

Do you have other preferred courses on these topics? If so, please leave the link for them in a comment, it would be really helpful to guide my students in the future.

And also as it seems that people is interested in these kind of courses summary , maybe I could repeat this post but posting a collection of useful Machine Learning and Deep Leaning courses and/or also cheminformatics courses. In relation with python for sure. Let’s see.