Data Science Grundlagen

What it is about

You will learn to load, explore, process, and visualize data and to apply basic statistical methods. In the end you will be able to implement data analysis workflows with Python (NumPy, pandas, SciPy) and accompanying tools, perform simple statistical adjustments, and provide results reproducibly.

What you will be able to do

Load dataset from disk in Python/Jupyter
Familiarity with numpy and pandas
Explore, transform and filter data
Visualize data distributions in low and high dimensions
Use statistical packages such as scipy
Compute descriptive statistics
Perform simple adjustments
Compute errors
Visualize statistical results
Basic knowledge of git
Publish a Python package on PyPI

What the module consists of

VorlesungTheoretical concepts and introduction of new tools and methods
ÜbungenPractical implementation of the lecture material in computer-based tasks

Teaching method

Vorlesungsblöcke (zweimal wöchentlich, 90 Minuten)Explanation of theoretical concepts and introduction of new tools
Anschließende ÜbungenPractice and application of the weekly material in practical tasks

Dates

LectureData Science Grundlagen2 groups to choose from

ATue10:00–12:00
2.103, Besprechung (5117.EG.103)
13× · 13.10.–02.02.
- 13.10.
- 27.10.
- 03.11.
- 17.11.
- 24.11.
- 01.12.
- 08.12.
- 15.12.
- 22.12.
- 12.01.
- 19.01.
- 26.01.
- 02.02.
ATue10:00–12:00PH 2024, Besprechungsraum E10/E12 (5101.EG.024)once on 20.10.
BWed14:00–16:00
PH 2024, Besprechungsraum E10/E12 (5101.EG.024)
15× · 14.10.–03.02.
- 14.10.
- 21.10.
- 28.10.
- 04.11.
- 11.11.
- 18.11.
- 25.11.
- 02.12.
- 09.12.
- 16.12.
- 23.12.
- 13.01.
- 20.01.
- 27.01.
- 03.02.

From the current semester, not binding. You attend one of several groups; the timetable automatically suggests the one with the fewest clashes.

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