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Advanced Computational Methods

SOT86050Electives6 ECTSEnglishwinter semesterDepartment Governance

In 2 fellow students' timetables

AI-edited module sheet. Based on the TUMonline module description, edited for readability.Original in TUMonline

What it is about

You will learn how to analyze large datasets — in particular text and network data — with Python. By the end you can collect, clean, transform and analyze data with standard libraries; moreover you will apply basic statistics, visualization and machine learning methods to your own research questions.

What you will be able to do

  • Data collection and reading (including web scraping and APIs)
  • Selecting, cleaning, merging and reshaping data
  • Text analysis: preprocessing, POS, NER, vectorization, topic modeling
  • Network analysis: metrics, centrality, diffusion simulations
  • Application of statistical methods (correlation, t-test, chi-squared)
  • Application of basic ML methods: regression, classification, clustering

What the module consists of

  • VorlesungPresentation of new topics and concepts
  • Übung / In‑class exercisesPractical implementation and application of the concepts in Python

Teaching method

  • VorlesungIntroduction to new topics
  • In‑class ÜbungenImplementation and application of the presented methods in Python

Dates

Seminar(SOT86050) Advanced Computational Methods

  • Mon13:15–16:30H.103, CIP-Raum (2910.01.103)
    15× · 12.10.–01.02.
    • 12.10.
    • 19.10.
    • 26.10.
    • 02.11.
    • 09.11.
    • 16.11.
    • 23.11.
    • 30.11.
    • 07.12.
    • 14.12.
    • 21.12.
    • 11.01.
    • 18.01.
    • 25.01.
    • 01.02.

From the current semester, not binding.

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Official page in TUMonline · Details are not binding.