Project studies 3 - Applying artificial intelligence (5 cr)
Code: TT00CC69-3001
General information
Enrollment
01.12.2023 - 31.01.2024
Timing
01.01.2024 - 27.05.2024
Number of ECTS credits allocated
5 op
Mode of delivery
Contact teaching
Unit
Teknologia
Teaching languages
- Finnish
Degree programmes
- Bachelor’s Degree in Information and Communication Technology
Teachers
- Tommi Kauppinen
- Pekka Huttunen
Groups
-
TTM22SAITTM22SAI
- 18.03.2024 17:00 - 20:00, Hybridiopetus_Projektiopinnot 3 - Tekoälyn soveltaminen TT00CC69-3001
- 25.03.2024 17:00 - 20:00, Hybridiopetus_Projektiopinnot 3 - Tekoälyn soveltaminen TT00CC69-3001
- 15.04.2024 17:00 - 20:00, Hybridiopetus_Projektiopinnot 3 - Tekoälyn soveltaminen TT00CC69-3001
- 29.04.2024 17:00 - 20:00, Hybridiopetus_Projektiopinnot 3 - Tekoälyn soveltaminen TT00CC69-3001
- 13.05.2024 17:00 - 20:00, Hybridiopetus_Projektiopinnot 3 - Tekoälyn soveltaminen TT00CC69-3001
- 27.05.2024 17:00 - 20:00, Hybridiopetus_Projektiopinnot 3 - Tekoälyn soveltaminen TT00CC69-3001
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
Evaluation scale
0 - 5
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.
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.
Prerequisites
Project studies 2 - Machine learning applications
Deep learning 1