Course unit, curriculum year 2026–2027
DATA.ML.370
Mining of Big Datasets, 5 cr
Tampere University
- Description
- Completion options
Teaching periods
Active in period 3 (1.1.2027–7.3.2027)
Active in period 4 (8.3.2027–31.5.2027)
Course code
DATA.ML.370Language of learning
English, FinnishAcademic years
2024–2025, 2025–2026, 2026–2027Level of study
Intermediate studiesGrading scale
General scale, 0-5Persons responsible
Responsible teacher:
Tarmo LippingResponsible teacher:
Jari TurunenResponsible organisation
Faculty of Information Technology and Communication Sciences 100 %
Coordinating organisation
Computing Sciences Studies 100 %
Core content
- The concept and terminology of data mining.
- Understanding the principles of processing large, non-structured datasets.
- Basic methods and algorithms for the analysis of large datasets
- Common tasks of mining large datasets such as similarity analysis, link analysis, finding frequent itemsets, clustering
- Common applications of mining large datasets such as recommendation systems, web search, mining of social network graphs
Complementary knowledge
- Mining data streams
- Special challenges of processing large datasets: memory usage and data formats.
- Deep learning methods in mining large datasets
Specialist knowledge
- Mapreduce algorithm.
- Locality-sensitive hashing
- Distance measures
- More advanced algorithms for mining large datasets
Learning outcomes
Prerequisites
Further information
Learning material
Studies that include this course
Completion option 1
The course will involve exercises and Teams discussions
Independent study
Online or distance self learning
11.01.2027 – 30.05.2027
Active in period 3 (1.1.2027–7.3.2027)
Active in period 4 (8.3.2027–31.5.2027)