Arvutiteaduse instituut
Courses.cs.ut.ee Arvutiteaduse instituut Tartu Ülikool
  1. Kursused
  2. 2026/27 sügis
  3. Andmetehnika (LTAT.02.007)
EN
Logi sisse

Andmetehnika 2026/27 sügis

  • Pealeht
  • Loengud
  • Viited
  • Hindamine

Grading

The course is graded out of 100 points:

  • 85p Project (groups of 4–5 students)
    • 15p Project Part 1
    • 5p peer grading for Project Part 1
    • 15p Project Part 2
    • 5p peer grading for Project Part 2
    • 15p Project Part 3
    • 5p peer grading for Project Part 3
    • 25p final poster session
  • 15p Lecture quizzes
    • 6 quizzes, 2.5p each

There is no final exam.

The quizzes are associated with the pre-recorded lectures. Each quiz must be completed after the lecture and before the corresponding practice session.

To pass the course, you need at least 51 points in total.

Passing grades:

  • A 91-100p
  • B 81-90p
  • C 71-80p
  • D 61-70p
  • E 51-60p
  • F 0-50p

Projects

The project should demonstrate the development of an end-to-end data engineering product.

Projects are completed in fixed groups of 4–5 students and consist of three parts:

  • Part 1: Dataset selection and project proposal design
  • Part 2: Conceptual model and data architecture
  • Part 3: Project Finalization and Presentation

The three parts are incremental: together, they should describe and implement a coherent data engineering product rather than three independent assignments.

Each project part is worth 15 points. In addition, each part includes a 5-point peer-grading component.

Timeline:

DateActivity
2026-09-28Project Part 1 deadline: Dataset selection and project proposal design
2026-11-02Project Part 2 deadline: Conceptual model and data architecture
2026-12-21Project Part 3 deadline: Project Finalization and Presentation
2027-01-18 16:15Final poster session (in person)

All times are in current Estonian time. Exact submission deadlines and peer-grading deadlines are specified on Moodle.

Poster Session

The final project assessment takes the form of a poster session on 18 January 2027 at 16:15.

Participation in the poster session is physical and mandatory.

Each group must prepare a poster presenting the complete project, including the problem and dataset, data model and architecture, implementation, and final results.

During the poster session, groups will present their work and discuss it with the teaching staff.

The poster session is worth 25 points.

Examples of posters, the required poster format, and detailed evaluation criteria will be provided on Moodle.

  • Arvutiteaduse instituut
  • Loodus- ja täppisteaduste valdkond
  • Tartu Ülikool
Tehniliste probleemide või küsimuste korral kirjuta:

Kursuse sisu ja korralduslike küsimustega pöörduge kursuse korraldajate poole.
Õppematerjalide varalised autoriõigused kuuluvad Tartu Ülikoolile. Õppematerjalide kasutamine on lubatud autoriõiguse seaduses ettenähtud teose vaba kasutamise eesmärkidel ja tingimustel. Õppematerjalide kasutamisel on kasutaja kohustatud viitama õppematerjalide autorile.
Õppematerjalide kasutamine muudel eesmärkidel on lubatud ainult Tartu Ülikooli eelneval kirjalikul nõusolekul.
Courses’i keskkonna kasutustingimused