Study program: F3 Computer Science

Degree: Master

Type of module: lectures, practical work

Lecturer: Seniour lecturer Oleksandra Putiatina

Language: English

Credit Points: 5 ECTS

Description:
The mandatory discipline of basic 
training includes the following topics:
1. Basic concepts, functions of big data.
2. The life cycle of data analytics.
3. Technologies for working with big data
4. Classification of data analysis tasks
5. The CRISP-DM methodology and stages
of the data mining process.
6. The Process of Data Mining.
7. Data Mining Tasks.
8. Data Mining Tasks: searching for
associative rules.
9. Means of visual representation of data.
Data visualization.
10.Data Mining Tasks. Classification and
Classification Methods.
11.Data Mining Tasks. Linear Classification
Methods.
12. Support vector method.
13. Model development and averaging.
14. Additive models, trees.
15. Tree-based methods.
16. Unsupervised Learning (Part 1).
17 Unsupervised Learning (Part 2).
18. Neural networks.