Databases
General information
Course code: LTAT.02.021
Volume: 6 ECTS (156 hours)
Semester: Autumn 2026
Language of instruction: English
Level: Master's and doctoral studies
Objectives
The course equips students with essential knowledge and practical skills in databases, enabling them to design, implement, and optimize database-driven applications. It covers the full lifecycle of database development, starting from conceptual design using entity-relationship (ER) modeling, progressing through logical design and normalization, and continuing to query formulation using relational algebra and SQL. The course also introduces key operational concepts of relational databases, including transactions, concurrency, indexing, and query optimization, and provides an overview of modern data management approaches, including NoSQL systems. Through labs and project work, students gain hands-on experience in applying database concepts in real-world scenarios.
Learning outcomes
Students gain a general understanding of:
- the design of relational databases, including ER modeling, the relational model, ER-to-relational mapping, and normalization;
- relational query languages, including relational algebra and SQL;
- transactions, concurrency, indexing, query plans, and basic query optimization; and
- the role of NoSQL systems in Big Data contexts.
Brief description of content
- Database design: ER modeling, the relational model, logical mapping, and normalization
- Relational algebra and SQL
- Transactions and concurrency
- Indexing, query plans, and basic query optimization
- Big Data and NoSQL systems
- Project work
Course sequence
- Introduction to Databases
- Entity-Relationship Modeling
- Relational Model and ER-to-Relational Mapping
- Functional Dependencies and Normalization
- Relational Algebra
- SQL Fundamentals
- Advanced SQL and Constraints
- Project Discussion and Full-Stack Labs
- Transactions and Concurrency
- Indexes, Query Plans, and Basic Query Optimization
- Big Data and NoSQL
- NoSQL Examples: MongoDB and Neo4j
- Project Work and Support
- Project Presentations
- Final Assessment
Assessment
The course uses a differentiated assessment scale (A-F). The final grade consists of the following components:
- Quizzes: 15%
- Homework assignments: 15%
- Final written exam: 40%
- Project: 30%
The following grading scale applies:
- A: 91-100%
- B: 81-90%
- C: 71-80%
- D: 61-70%
- E: 51-60%
- F: 0-50%
Meeting days and times
Lectures: Wednesday, 10:15-12:00, Delta Centre, room 2045
Practical classes: Thursday, 14:15-16:00, Delta Centre, room 2030
Teaching staff
Miika Hannula - Course coordinator and lecturer
Riccardo Tommasini - Lecturer
Teymur Ismikhanov - Teaching assistant
Learning environment and support
The Moodle course page will be announced later (TBA).
When using artificial intelligence in this course, follow the University of Tartu guidelines for using AI applications in teaching and studies.
UniTartuCS IT support: ati.comp@ut.ee