Skip to main content

Artificial Intelligence Applications (5 cr)

Code: 5051253-3005

General information


Enrollment
04.12.2024 - 13.01.2025
Registration for the implementation has ended.
Timing
13.01.2025 - 30.04.2025
Implementation is running.
Number of ECTS credits allocated
5 cr
Local portion
5 cr
Mode of delivery
Contact learning
Unit
Engineering and Business
Campus
Kupittaa Campus
Teaching languages
Finnish
Seats
0 - 40
Degree programmes
Degree Programme in Information and Communication Technology
Teachers
Matti Kuikka
Pertti Ranttila
Groups
PTIVIS22H
Health Technology
Course
5051253

Realization has 12 reservations. Total duration of reservations is 36 h 0 min.

Time Topic Location
Wed 15.01.2025 time 09:00 - 12:00
(3 h 0 min)
Tekoälysovellukset 5051253-3005
EDU_1090 Ringsberg esitystila byod
Wed 22.01.2025 time 09:00 - 12:00
(3 h 0 min)
Tekoälysovellukset 5051253-3005
ICT_C2025 Kieliluokka
Wed 29.01.2025 time 09:00 - 12:00
(3 h 0 min)
Tekoälysovellukset 5051253-3005
EDU_1089 Maskulin esitystila byod
Wed 05.02.2025 time 09:00 - 12:00
(3 h 0 min)
Tekoälysovellukset 5051253-3005
EDU_1089 Maskulin esitystila byod
Wed 12.02.2025 time 09:00 - 12:00
(3 h 0 min)
Tekoälysovellukset 5051253-3005
EDU_1089 Maskulin esitystila byod
Wed 26.02.2025 time 09:00 - 12:00
(3 h 0 min)
Tekoälysovellukset 5051253-3005
EDU_1089 Maskulin esitystila byod
Wed 05.03.2025 time 09:00 - 12:00
(3 h 0 min)
Tekoälysovellukset 5051253-3005
EDU_1089 Maskulin esitystila byod
Wed 12.03.2025 time 09:00 - 12:00
(3 h 0 min)
Tekoälysovellukset 5051253-3005
EDU_3029 Lovisa muunto byod
Wed 19.03.2025 time 09:00 - 12:00
(3 h 0 min)
Tekoälysovellukset 5051253-3005
EDU_1089 Maskulin esitystila byod
Wed 26.03.2025 time 09:00 - 12:00
(3 h 0 min)
Tekoälysovellukset 5051253-3005
EDU_1089 Maskulin esitystila byod
Wed 02.04.2025 time 09:00 - 12:00
(3 h 0 min)
Quest Speaker Paulo Maio: Tekoälysovellukset 5051253-3005
EDU_3001 Kaarle muunto byod
Wed 09.04.2025 time 09:00 - 12:00
(3 h 0 min)
Tekoälysovellukset 5051253-3005
EDU_1089 Maskulin esitystila byod
Changes to reservations may be possible.

Evaluation scale

H-5

Content scheduling

Starting from week 3 and continuing weekly

The course covers the following topics:

Basics and fundamental concepts of artificial intelligence
Traditional programming vs. machine learning
Regression and classification
Principles of neural networks
Data and its characteristics in machine learning
Supervised and unsupervised machine learning methods and applications
Backpropagation algorithm
Functioning of the perceptron algorithm
Reinforcement learning methods and applications
Deep learning methods and applications
Decision trees
Applications of generative artificial intelligence
Production and characteristics of synthetic data

Objective

After completing the course the student:
- understands what the artificial intelligence is in social and health care
- can explain the basic concepts of artificial intelligence
- knows the available artificial intelligence applications in social and health care
- understands the possibilities and limitations of artificial intelligence in social and health care

Content

- Basics of Artificial Intelligence
- Artificial Intelligence Applications
- Neural networks
- Machine learning

Materials

The lecture material is mainly in English.

Lecture materials, exercises, and other resources will be distributed via ITS-learning.

Teaching methods

Lectures, code examples, and independent exercises

Exam schedules

The course exam can be retaken three times.

International connections

The course includes approximately 13 lectures or practice sessions.

Student workload

Contact hours in total: approximately 40 hours

Independent study and homework: 90 hours

Total: approximately 130 hours

Further information

Course announcements will be made via ITS-learning

Go back to top of page