Python for Biologists
Summary
The Python for Biologists course is the next evolution of the Python for Scientists & Engineers course tailored specifically to Biologists by including libraries like Biopython.
Biologists need programming skills in Python to analyze their data but have rarely had any programming education during their Bachelor’s and Master’s degrees. Hence, this course has four goals and teaches
- a basic introduction to Python and programming in general
- to analyze, interpret and visualize scientific data to create publication ready plots
- good programming practice, version control with GIT and virtual environments
- specialization in Biopython (DNA analysis), Image analysis, or more (see below)
There are different specialization modules which participants can choose from since biologists – even if working in the same workgroup – need different specializations depending on their research topic.
Target groups
The course is suited for people with previous experience in other programming languages and for people who already have experience with Python looking to improve their skills. A lot of previous participants have been self-taught and appreciated the structured introduction to Python.
The course is also suitable for absolute beginners in programming, however, beginners should plan to invest additional time between tutorials to learn fundamentals from the additional resources.
Course structure
The course is held in English and currently consists of 6 modules. It can be taken on-demand or as a blended learning course. The on-demand modules each contain
- a 60-90 minute video lecture that participants can watch when it suits them
- exercises for the participants to apply what they have learned
Content
Installation
Introduction, Jupyter, Virtual Environments, Notebook extensions, Python fundamentals
Basics
Syntax, PEP8, Keyboard shortcuts, Introduction to Numpy and Matplotlib
Advanced Numpy, Pandas, File Input & Output, ChatGPT
Advanced Matplotlib, Inset Plots, Contour Plots, Interactive Plots
GIT, String Formatting, Video Creation, Notebook Structure
Specializations
Interpolation, Fitting, Complex Fitting, Filtering, Data analysis example
File creation, Generators, Parallelization, Sympy, Integration of Plots to Overleaf
Biopython, DNA sequencing, BLAST, Visualization of DNA
Image Analysis and Processing (Scikit Image)
