Bachelor
2022/2023
Data management in intelligent systems
Type:
Elective course (Applied Mathematics and Information Science)
Area of studies:
Applied Mathematics and Information Science
Delivered by:
School of Data Analysis and Artificial Intelligence
Where:
Faculty of Computer Science
When:
3 year, 1, 2 module
Mode of studies:
offline
Open to:
everyone
Language:
English
ECTS credits:
5
Contact hours:
64
Course Syllabus
Abstract
One of the main methodological processes in the development of information technology is abstraction (more precisely, data abstraction, in contrast to the abstraction of processes) - consideration also caused a technologically distinguished subject area called "databases" (DB). It includes theory, methods and technologies: 1) formalization of conceptual, relationships and physical data of models; 2) development of universal languages, data manipulation;3) building database management systems (DBMS); 4) optimal access to data using a DBMS. The study of database theory is a necessary step before diving into knowledge representation, artificial intelligence methods and the construction of intelligent systems. The following five main sections can be distinguished in the discipline. 1. Information and data. Data abstraction and data models. Reasons and goals for creating a database and DBMS. The main characteristics of the database and DBMS. Problems that arise when describing data and manipulating them. 2. Formalization of subject area data and infological data models. The entity-relationship model. 3. Datalogical data models. Relational data model. Relational algebra and relational calculus. Relational databases and the SQL language. Beyond the relational model: NoSQL. 4. Database design, that is, the creation and optimization of a data schema using various DBMS. 5. Access to data in modern information systems. Interfaces and protocols. Architectures of information systems using DBMS, including multi-link and distributed ones.