Data Science I

Data Science I

The course provides a full introduction to data science with an emphasis on hands-on examples. Students will acquire relevant knowledge of the whole data science chain: From storage/acquisition to statistical inference, machine learning models to visualization. It also serves as an introductory course to the Data Science project seminar.


● This course is offered for the first time in Summer 2021.

● The lectures and tutorials will be conducted digitally via Zoom.

● The tutorials will be hands-on sessions, please get Jupyter notebook ready to run (e.g. by Anaconda or Google Colab) before the first session begins.

Course Overview

Prerequisites -
Language English
Schedule Lecture: Fridays 11:40 – 13:20 (weekly starting 16.04.2021)
Tutorial: Tuesdays 09:50 – 11:30 (weekly starting 20.04.2021)
Format Online via Zoom: Lecture and Tutorial (L2+T2), 5CP
Material Provided through Moodle (
FB18 Elektrotechnik und Informationstechnik – E: Data Science I 18-zo-2110-ue
Office Hours Dr.-Ing. Christian Debes: (by email appointment)
Pertami Kunz: (tba)
Lecture slides and tutorials from Moodle

● Wes McKinney: Python for Data Analysis, O’Reilly, 2017
● Christopher M. Bishop: Pattern Recognition and Machine Learning, 2011
● James, Witten, Hastie and Tibshirani, Introduction to Statistical Learning, Springer, 2017