Course unit, curriculum year 2024–2025
DATA.STAT.770
Dimensionality Reduction and Visualization, 5 cr
Tampere University
- Description
- Completion options
Teaching periods
Active in period 3 (1.1.2025–2.3.2025)
Active in period 4 (3.3.2025–31.5.2025)
Course code
DATA.STAT.770Language of instruction
EnglishAcademic years
2024–2025, 2025–2026, 2026–2027Level of study
Advanced studiesGrading scale
General scale, 0-5Persons responsible
Responsible teacher:
Tapio NummiResponsible teacher:
Jaakko PeltonenResponsible organisation
Faculty of Information Technology and Communication Sciences 100 %
Coordinating organisation
Computing Sciences Studies 100 %
Properties of high-dim data; Feature Selection; Linear feature extraction methods such as principal component analysis and linear discriminant analysis; Graphical excellence; Human perception; Nonlinear dimensionality reduction methods such as the self-organizing map and Laplacian embedding; Neighbor embedding methods such as stochastic neighbor embedding and the neighbor retrieval visualizer; Graph visualization; Graph layout methods such as LinLog.
Learning outcomes
Prerequisites
Learning material
Kokonaisuudet, joihin opintojakso kuuluu
Completion option 1
The course will be lectured on academic year 2024-2025 and 2026-2027 in 3rd and 4th period. To pass the course, you must pass the exam and complete a sufficient number of exercises from the exercise packs. Exercise packs will be released during the course.
Completion of all options is required.
Exam
07.01.2025 – 31.05.2025
Active in period 3 (1.1.2025–2.3.2025)
Active in period 4 (3.3.2025–31.5.2025)
Participation in teaching
07.01.2025 – 31.05.2025
Active in period 3 (1.1.2025–2.3.2025)
Active in period 4 (3.3.2025–31.5.2025)