Datan louhinta ja avoin dataLaajuus (5 op)

Osaamistavoitteet

The student understands the basic concepts, principles, methods and implementation techniques of data mining. The student outlines the philosophy of open data and is capable to utilize and visualize it.

Sisältö

- Open data
- Pattern recognition in data mining
- Cluster analysis / Unsupervised machine learning
- Data Lakes / Data Fabrics / Data Warehouse
- Text mining / Sentiment analysis (opinion mining / emotion AI)
- Data visualisation in dashboards
- Legislation and ethical issues

Arviointikriteerit, tyydyttävä (1)

Student knows the main concept of data mining. Student outlines the principles of open data. The student understands the key legal and ethical issues in open data and data mining context.

Arviointikriteerit, hyvä (3)

The student understands the foundation of data mining. The student can apply proper implementation methods and techniques for data mining. The student can apply open data in practical application development and take into account key legal and ethical issues.

Arviointikriteerit, kiitettävä (5)

The student deeply understands the concept, principles, methods and techniques of data mining. The student can utilize and visualize open data in wider practical application development. The student can select proper implementation methods and techniques in challenging data mining application development. The student deeply understands the key legal and ethical issues in open data and data mining context and can take them into account in practice.