Big Data Systems
Description: The course is aimed at studying the methods and technologies used for managing and analyzing large volumes of data. It covers concepts, architecture components, and tools applied in the field of big data; the application of key Data Mining technologies and tools for extracting valuable information and identifying trends from large datasets. The practical skills acquired will enable the presentation of experimental data results in dissertation research in scientific journals and experimental research reports.
Amount of credits: 5
Пререквизиты:
- Introduction to Data Mining methods
Course Workload:
| Types of classes | hours |
|---|---|
| Lectures | 15 |
| Practical works | |
| Laboratory works | 30 |
| SAWTG (Student Autonomous Work under Teacher Guidance) | 75 |
| SAW (Student autonomous work) | 30 |
| Form of final control | Exam |
| Final assessment method |
Component: Component by selection
Cycle: Profiling disciplines
Goal
- The aim of the course is to introduce students to modern methods of analyzing "big data". The acquired knowledge and skills will help students improve the quality of decision-making through the correct collection, structuring and use of modern techniques for analyzing large volumes of data.
Learning outcome: knowledge and understanding
- Знание основных концепции и принципов больших данных, архитектуру и компонентов систем больших данных, знание современных технологий и инструментов, используемых для работы с большими данными.
Learning outcome: applying knowledge and understanding
- Analysis and assessment of data quality, selection of technologies and tools, ability to interpret and evaluate the results of big data analysis to support decision making.
Learning outcome: formation of judgments
- The ability to assess the quality, reliability and relevance of data, to present ideas, to argue and prove logically, the ability to draw conclusions and make informed decisions.
Learning outcome: communicative abilities
- Ability to clearly and structured describe the completed stages of work, the methods used and the results obtained, answer questions, and argue your position based on data.
Learning outcome: learning skills or learning abilities
- Ability to analyze various sources of information, ability to master new approaches and methods of data analysis and tools used to work with big data.
