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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

  • TTM22SAI
    TTM22SAI
  • 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