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Project studies 3 - Applying artificial intelligence (5cr)

Code: TT00CC69-3004

General information


Enrollment
30.12.2025 - 26.01.2026
Registration for the implementation has begun.
Timing
01.01.2026 - 31.07.2026
Implementation is running.
Number of ECTS credits allocated
5 cr
Unit
Teknologia
Teaching languages
Finnish
Degree programmes
Bachelor’s Degree in Information and Communication Technology
Teachers
Tommi Kauppinen
Liisa Majuri
Groups
TTM24SAI
TTM24SAI
Course
TT00CC69

Realization has 5 reservations. Total duration of reservations is 15 h 0 min.

Time Topic Location
Tue 17.03.2026 time 17:00 - 20:00
(3 h 0 min)
Ohjaustuokio & Tehtävänanto_Projektiopinnot 3 - Tekoälyn soveltaminen TT00CC69-3004
Teams
Tue 14.04.2026 time 17:00 - 20:00
(3 h 0 min)
Ohjaustuokio & Suunn.esit.1_Projektiopinnot 3 - Tekoälyn soveltaminen TT00CC69-3004
Teams
Tue 21.04.2026 time 17:00 - 20:00
(3 h 0 min)
Ohjaustuokio & Suunn.esit.2_Projektiopinnot 3 - Tekoälyn soveltaminen TT00CC69-3004
Teams
Tue 12.05.2026 time 17:00 - 20:00
(3 h 0 min)
Ohjaustuokio & Työnesit.1_Projektiopinnot 3 - Tekoälyn soveltaminen TT00CC69-3004
Teams
Tue 19.05.2026 time 17:00 - 20:00
(3 h 0 min)
Ohjaustuokio & Työnesit.2_Projektiopinnot 3 - Tekoälyn soveltaminen TT00CC69-3004
Teams
Changes to reservations may be possible.

Evaluation scale

0 - 5

Objective

Customer projects are continued in the third AI project course. In this course, the goal is to receive data from the company and a research question, to which the answer is to be found using artificial intelligence.

In addition, the course adds a design component by making a project plan and an architectural plan at the beginning of the project.

Content

1. Planning
- A project plan is made from the project
- The project's data processing architecture plan
2. Data preprocessing
- Data is stored in the database/version control
- The data is pre-processed in such a way that it can be fed to artificial intelligence algorithms
3. Prediction using artificial intelligence
- Algorithms to be tested for prediction are selected
- We test the operation of the selected algorithms
- We will report the results
4. Possible adjustment if the prediction is successful
- We select the algorithms to be tested for adjustment
- We test the operation of the selected algorithms
- We will report the results

Assessment criteria, satisfactory (1)

The student group is expected to complete the project until the end.
- The group has completed the returns for all project subtasks at the latest on the last return day of the course at a satisfactory level.
- In addition, the student group is able to demonstrate sufficient working time spent on the project and that they are able to work as a team.

Assessment criteria, excellent (5)

Commendable performance is expected from the student group in the following areas:
- Use of the SCRUM method, communication and teamwork
- Project deliveries have been made on time
- Quality of project reports
- The results obtained in the project and their meritorious reflection.

Qualifications

Project studies 2 - Machine learning applications
Deep learning 1

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