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Course unit, curriculum year 2024–2025
DATA.ML.390
Computational Diagnostics of Data, 5 cr
Tampere University
- Description
- Completion options
Teaching periods
Active in period 1 (1.8.2024–20.10.2024)
Active in period 4 (3.3.2025–31.5.2025)
Active in period 5 (1.6.2025–31.7.2025)
Course code
DATA.ML.390Language of instruction
EnglishAcademic years
2024–2025, 2025–2026, 2026–2027Level of study
Advanced studiesGrading scale
General scale, 0-5Persons responsible
Responsible teacher:
Frank Emmert-StreibResponsible organisation
Faculty of Information Technology and Communication Sciences 50 %
Faculty of Medicine and Health Technology 50 %
Coordinating organisation
Computing Sciences Studies 100 %
Core content
General error measures
Statistical hypothesis testing
Classification models
Resampling methods
Regression models
Survival analysis
Examples for complex data
Programming in R
Complementary knowledge
Statistical thinking
Introduction to programming in R
Data analysis is unlike following a cookbook recipe
Learn about different data types
Evaluating results requires different statistical error measures
Resampling techniques allow the quantification of uncertainty
Learning outcomes
Prerequisites
Further information
Learning material
Equivalences
Studies that include this course
Completion option 1
In English.
Completion of all options is required.
Participation in teaching
03.03.2025 – 27.04.2025
Active in period 4 (3.3.2025–31.5.2025)
Exam
12.08.2024 – 18.08.2024
Active in period 1 (1.8.2024–20.10.2024)
28.04.2025 – 04.05.2025
Active in period 4 (3.3.2025–31.5.2025)
02.06.2025 – 08.06.2025
Active in period 5 (1.6.2025–31.7.2025)