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Course unit, curriculum year 2024–2025
DATA.ML.390

Computational Diagnostics of Data, 5 cr

Tampere University
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.390
Language of instruction
English
Academic years
2024–2025, 2025–2026, 2026–2027
Level of study
Advanced studies
Grading scale
General scale, 0-5
Persons responsible
Responsible teacher:
Frank Emmert-Streib
Responsible 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)