Big Data Systems Development and Implementation
Description: This course is a foundational piece of the skill set for data analytics. It helps the analyst to find trends in data at a high level, and transform it into a functional commodity. For the study of very large data sets, the course will teach data mining algorithms. It will have an applied focus; it is intended to train students to use data mining topics to solve challenges in the real world.
Amount of credits: 6
Пререквизиты:
- Current Programming Media and Languages
- Machine Learning and Data Analysis
Course Workload:
| Types of classes | hours |
|---|---|
| Lectures | 30 |
| Practical works | |
| Laboratory works | 30 |
| SAWTG (Student Autonomous Work under Teacher Guidance) | 30 |
| SAW (Student autonomous work) | 90 |
| Form of final control | Exam |
| Final assessment method |
Component: Component by selection
Cycle: Profiling disciplines
Goal
- The purpose of the course is to gain an understanding of the capabilities and constraints of data mining and machine learning algorithms for the study of very large data sets and to recognise promising data mining market applications.
Objective
- understand the value of data mining and machine learning for analyzing very large data sets in solving real-world problems
- understand foundational concepts underlying data mining and machine learning for analyzing very large data sets
- understand algorithms commonly used in data mining tools
- be able to apply data mining tools to real-world problems
Learning outcome: knowledge and understanding
- demonstrate advanced knowledge of data mining and machine learning algorithms concepts and techniques for analyzing very large data sets
Learning outcome: applying knowledge and understanding
- apply the techniques of clustering, classification, association finding, feature selection and visualization on real-world data
Learning outcome: formation of judgments
- determine whether a real world problem has a data mining solution
Learning outcome: communicative abilities
- demonstrate knowledge of the ethical considerations involved in data mining and machine learning for analyzing very large data sets
Learning outcome: learning skills or learning abilities
- set up a data mining process for an application, including data preparation, modelling and evaluation
Key reading
- Rajaraman, J. Leskovec and J. D. Ullman, Mining of Massive Datasets, 2nd Edition.
