Institute of Computer Science
  1. Courses
  2. 2025/26 fall
  3. Data Engineering (LTAT.02.007)
ET
Log in

Data Engineering 2025/26 fall

  • Pealeht
  • Loengud
  • Viited
  • Hindamine

Most of the lecture and practice session material can be found on Moodle and on GitHub: https://github.com/DataSystemsGroupUT/data_engineering_2025

The course schedule (classes) for 2025:

WeekLectureTopicPracticeTopicDeadline
12025-09-01No class2025-09-02No class 
22025-09-08Introduction2025-09-09Docker, Postgres 
32025-09-15Data architecture, data modeling2025-09-16ER diagrams 
42025-09-22Dimensional modeling2025-09-23Star schema 
52025-09-29Data Engineering Design Patterns (Prerecorded)2025-09-30-Project 1 (2025-10-05)
62025-10-06Data processing and orchestration2025-10-07AirflowP1 peer grading (2025-10-12)
72025-10-13Data storage, OLAP2025-10-14ClickHouse 
82025-10-20Data transformation2025-10-21dbt 
92025-10-27Semi-structured data2025-10-28MongoDBProject 2 (2025-11-02)
102025-11-03Data Lakes2025-11-04Apache IcebergP2 peer grading (2025-11-09)
112025-11-10Security & Privacy2025-11-11Masking, RBAC 
122025-11-17Data Governance2025-11-18Open Metadata 
132025-11-24Data Visualization2025-11-25Apache SupersetProject 3 (2025-11-30)
142025-12-01Guest lecture (TBD)2025-12-02Exam prepProject poster, P3 peer grading (2025-12-07)
152025-12-08Exam 1*2025-12-09Exam 2* 
162025-12-15Project presentations*2025-12-16Exam redo* 

Both lectures and practice times are 16:15-18:00, except when otherwise noted via Moodle by the teaching staff.

Exams: you choose either option 1 or option 2. If you fail the exam, OR you have doctor's written confirmation on illness, then you can take the exam redo. Redo is not possible for cases when you are not satisfied with your initial passing grade.

All classes take place physically in the classroom noted in OIS, unless otherwise noted via Moodle by the teaching staff.

There will be a Zoom recording/participation available for most classes, but online participation is not fully supported.

  • NB! for exams and final project presentation, physical participation is mandatory.
  • Institute of Computer Science
  • Faculty of Science and Technology
  • University of Tartu
In case of technical problems or questions write to:

Contact the course organizers with the organizational and course content questions.
The proprietary copyrights of educational materials belong to the University of Tartu. The use of educational materials is permitted for the purposes and under the conditions provided for in the copyright law for the free use of a work. When using educational materials, the user is obligated to give credit to the author of the educational materials.
The use of educational materials for other purposes is allowed only with the prior written consent of the University of Tartu.
Terms of use for the Courses environment