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Root number
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473540 |
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Semester
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FS2026 |
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Type of course
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Lecture |
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Allocation to subject
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Bioinformatics |
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Type of exam
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Written exam |
| Title |
Introduction to data science with Python. With practicals. |
| Description |
This course provides a practical introduction to programming for data science with Python. It targets students who want to work with real datasets, write reliable and readable code, and understand the computational foundations of modern data analysis.
The course starts with core Python concepts and the structure of the Python runtime, followed by the main tools of the data science ecosystem: NumPy for numerical computing, Pandas for data handling, and Matplotlib for data visualization. Students learn how to efficiently manipulate data, explore datasets, and build structured data-analysis workflows.
The Machine Learning block covers core concepts such as regression, loss functions, optimization, and model evaluation, with practical exercises in scikit‑learn.
The fundamentals of neural networks are introduced, and multilayer neural networks are implemented in PyTorch. Convolutional and Transformer models are presented conceptually and illustrated with brief PyTorch examples.
The course concludes with essential software engineering practices for data science, including version control, and examines a real‑world ML application used at SBB. Homework assignments and small projects provide hands-on experience. After completing the course, students can read, write, and reason about data science code and apply fundamental machine learning methods in a controlled and reproducible way. |
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ILIAS-Link (Learning resource for course)
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Registrations are transmitted from CTS to ILIAS (no admission in ILIAS possible).
ILIAS
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Link to another web site
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| Lecturers |
Dr.
Markus Anwander, Institute of Computer Science ✉
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Prof. Dr.
Athina Tzovara, Institute of Computer Science ✉
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ECTS
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5 |
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Recognition as optional course possible
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Yes |
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Grading
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1 to 6 |
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| Dates |
Thursday 14:15-17:00 Weekly
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Thursday 2/4/2026 14:15-17:00
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Thursday 7/5/2026 14:15-17:00
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Thursday 11/6/2026 14:15-16:00
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Thursday 3/9/2026 14:15-16:00
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Rooms
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| External rooms |
Hörsaal B006, Exakte Wissenschaften, ExWi
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Room 205, Hochschulstrasse 4 (main building)
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seminar room 215, main building, Hochschulstrasse 4
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| Students please consult the detailed view for complete information on dates, rooms and planned podcasts. |
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