• Genome Data Science

    We develop methods and tools to work with tens of thousands of genomes and analyze and integrate the corresponding data.

    Model of DNA double helix in front of a student.
    © Universität Bielefeld

Programming


392168/392169 Schönhuth, Pianesi Winter 2025/26 Wed 14:00-16:00 S1-500 (V) and Thu 10:00-12:00 D2-152 (Ü)

Contents

Data Science is an emerging interdisciplinary field with the aim to extract information from prevalently unstructured data. A basic skill for every data scientist is programming.

This course sets out to introduce Python, a modern object-oriented programming language, to prospective data scientists. The class covers basic programming skills and provides an introduction to computer science. In the second part, Python libraries and tools are presented that are handy in the daily life of a data scientist, such as Jupyter Notebook, NumPy, Pandas, Matplotlib, Scikit-Learn, and Pyspark.

No prior knowledge of computer science is required, but basic training in mathematics is assumed.


This class will be taught on site and online via Zoom.
Tutorials are offered on site and online via Zoom.

Literature

Contact

Time table lecture

Date Topic Discussion Exercise Upload
05.11.2025 Organizational matters, intro to programming and ChatGPT (slides) Exercise 00 (file)
12.11.2025 Programming and Python basics (slides) Exercise 01 (file)
18.11.2025 Data types, arithmetic operations & Conditions, comparisons (slides) Exercise 02 (file)
25.11.2025 Loops (slides) Exercise 03 (file)
03.12.2025 Functions, debugging & Functional programming, lazy evaluation (slides) Exercise 04 (file)
10.12.2025 Object oriented Programming (slides) Exercise 05 (file)
17.12.2025 Input, processing of files and Text Mining (slides) Exercise 06 (file)
24.12.2025 Christmas Break
07.01.2026 Data visualization and NumPy (slides) Exercise 07 (file)
14.01.2026 Pandas (slides) Exercise 08 (file)
21.01.2026 Machine Learning (slides) Exercise 09 (file)
28.01.2026 ML (continued) + Advanced topic 1 - Neural networks with PyTorch
04.02.2026 First exam
04.03.2026 Second exam

Time table tutorial

Date Exercise Discussion
06.11.2025 Intro from ground up
13.11.2025 Exercise 00, ChatGPT & Scratch
20.11.2025 Exercise 01, Python basics
27.11.2025 Exercise 02, Data types & more
04.12.2025 Exercise 03, Loops
11.12.2025 Exercise 04, Functions & more
18.12.2025 Exercise 05, OOP
08.01.2026 Exercise 06, I/O
15.01.2026 Exercise 07, NumPy
22.01.2026 Exercise 08, Pandas
29.01.2026 Mock exam walkthrough
29.01.2026 Exercise 09, ML