PLA-43106 Data Mining, 5 cr
Person responsible
Teemu Kumpumäki, Pekka Ruusuvuori
Lessons
Implementation 1: PLA-43106 2015-01
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Requirements
Active participation and successful completion of exercise works.
Completion parts must belong to the same implementation
Learning Outcomes
The course gives an introduction to data mining and analysis of large datasets. For example, networks and databases involve massive amounts of data, and mining of useful information from data is an increasingly common challenge. By taking the course, the student learns the basic principles and terminology of data mining, knows the commonly used algorithms, and recognizes the typical challenges of processing large datasets. The course will introduce several application areas of data mining, including the principles of web search engines, recommendation systems, and web advertising.
Content
| Content | Core content | Complementary knowledge | Specialist knowledge |
| 1. | The concept and terminology of data mining. | Knowledge of the basic methods and algorithms. | Knowledge of the limitations of data mining. |
| 2. | Understanding the special principles of processing large, non-structured datasets. | Special challenges of processing large datasets: memory usage and data formats. | Mapreduce algorithm. |
| 3. | Basic principles of web search engines. |
Study material
| Type | Name | Author | ISBN | URL | Additional information | Examination material |
| Book | Mining of Massive Datasets | A. Rajaraman, J. Leskovec, J.D. Ullman | Yes | |||
| Lecture slides | P. Ruusuvuori | Yes |
Correspondence of content
There is no equivalence with any other courses