Summary of course content

Python is one of the most widely used and fastest-growing programming languages in both academia and industry. This course introduces students to core Python programming concepts — including loops, conditional statements, functions, bioinformatics pipelines, and data visualization — with a focus on practical applications in biomedical research.

Biomedical data scientists use Python for data analysis, building custom functions, and developing reusable packages that can be shared with the broader research community. This course is specifically tailored to the training background of biologists, assuming no prior programming experience.

Modern high-throughput technologies generate vast amounts of genomic, transcriptomic, proteomic, and metabolomic data that cannot be efficiently analyzed by hand. The ability to write scripts and automated pipelines is therefore an essential skill for any researcher working in these fi elds. Python is particularly well-suited for this purpose: it is beginner-friendly and highly readable, yet powerful enough to support statistical analysis, machine learning, and data visualization through its extensive ecosystem of scientific packages.

Aims & objectives

By the end of this course, students will have the foundational skills to independently explore biological datasets, automate repetitive analyses, and continue their journey into computational biology with confidence.

Syllabus

Getting Started: Introduction
Displaying Text
String Variables
Storing numbers
Working with dates and times
Making decisions with code
Complex decisions with code
Repeating events until done
Remembering lists
Save information in fi les
Reading from fi les
Functions
Handling errors
From Problem to Code – a Message Converter as an Example
Group Project in Biological Science

Assessment