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Project studies 3 - Applying artificial intelligence (5 cr)

Code: TT00CC69-3001

General information


Enrollment
01.12.2023 - 31.01.2024
Registration for the implementation has ended.
Timing
01.01.2024 - 27.05.2024
Implementation has ended.
Number of ECTS credits allocated
5 cr
Local portion
5 cr
Mode of delivery
Contact learning
Unit
Teknologia
Teaching languages
Finnish
Degree programmes
Bachelor’s Degree in Information and Communication Technology
Teachers
Tommi Kauppinen
Pekka Huttunen
Groups
TTM22SAI
TTM22SAI
Course
TT00CC69

Realization has 4 reservations. Total duration of reservations is 12 h 0 min.

Time Topic Location
Mon 15.04.2024 time 17:00 - 20:00
(3 h 0 min)
Hybridiopetus_Projektiopinnot 3 - Tekoälyn soveltaminen TT00CC69-3001
Keilaranta 14, Espoo Keilaranta 14, Espoo
Mon 29.04.2024 time 17:00 - 20:00
(3 h 0 min)
Hybridiopetus_Projektiopinnot 3 - Tekoälyn soveltaminen TT00CC69-3001
Keilaranta 14, Espoo Keilaranta 14, Espoo
Mon 13.05.2024 time 17:00 - 20:00
(3 h 0 min)
Hybridiopetus_Projektiopinnot 3 - Tekoälyn soveltaminen TT00CC69-3001
Keilaranta 14, Espoo Keilaranta 14, Espoo
Mon 27.05.2024 time 17:00 - 20:00
(3 h 0 min)
Hybridiopetus_Projektiopinnot 3 - Tekoälyn soveltaminen TT00CC69-3001
Keilaranta 14, Espoo Keilaranta 14, Espoo
Changes to reservations may be possible.

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

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