This three-day course is designed to provide the foundations and typical workflow of data science, with a particular focus on biology and life sciences, using the Python programming language. Throughout the course, participants will learn intermediate to more advanced concepts of Python programming and engage in hands-on coding exercises.

The course is intended for biologists and life scientists at all levels with some prior programming experience and basic knowledge of Python (general syntax, variables, lists, dictionaries, conditionals, loops, functions).

By the end of the course, participants will be able to:

- understand the different steps of a data science workflow in biology
- write Python code for data wrangling and interaction with common bioinformatics formats
- understand the basics of machine learning using Python
- understand the principles of data visualization with applications in Python

Monday– Classes from 2-6 PM Berlin time

- Intermediate Python: classes, requests, exception handling, tips & tricks
- BioPython: Python meets bioinformatics
- Pandas: Data wrangling

Tuesday– Classes from 2-6 PM Berlin time

Machine learning:

- Intro and theoretical foundations
- Supervised, unsupervised, and reinforcement learning
- Commonly used algorithms
- Feature engineering and selection
- Train-test split and cross-validation
- Hands-on with scikit-learn

 
Wednesday– Classes from 2-6 PM Berlin time

Data visualization:

- introduction and theoretical concepts
- principles and common errors
- Hands-on with Python plotting libraries such as matplotlib and seaborn

Should you have any further questions, please send an email to info@physalia-courses.org