back to search

Analyzing Text Data: From Basics to Advanced Techniques

SOT86069Specialization in Technology6 ECTSEnglishsummer semesterDepartment Governance
AI-edited module sheet. Based on the TUMonline module description, edited for readability.Original in TUMonline

What it is about

The module teaches techniques for analyzing text data from the basics to modern methods. You will learn to prepare and present texts, apply classical and modern methods such as classification, topic modeling, sentiment analysis as well as transformer and large language models in practice. In the end you will be able to implement text analyses in Python on real datasets and derive insights from them.

What you will be able to do

  • Master text preprocessing
  • Create text representations
  • Apply NLP methods
  • Conduct text classification
  • Conduct sentiment analysis
  • Employ topic modeling
  • Use text embeddings and word vectors
  • Integrate transformers and large language models
  • Practical implementation in Python

What the module consists of

  • VorlesungDelivery of the respective topics and contents from the field of text analysis
  • ÜbungImplementation and application of the presented methods in Python

Teaching method

  • Lecture with integrated exercisesPresentation of the theory in the lecture part and practical implementation in the exercise part
No dates in the current semester
There are no course dates for this module this semester, or they haven't been matched yet.

Module ratings

No ratings for this module yet.

Rate this module

Only fill in the categories you can judge – for each one, either stars and text together or nothing at all.

Lecture
Tutorial
Exam

Reviews are automatically checked before they are published.

Official page in TUMonline · Details are not binding.