Study Guide

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

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

Further information

Course announcements will be made via ITS-learning

Evaluation scale

H-5

Assessment methods and criteria

Assessment is on a scale of 0 to 5.

To pass the course, you must successfully complete the exam. The passing threshold for the exam is at least 40% of the maximum points. The passing grades are evenly distributed between 40% and 100%.

It is possible to earn additional points from exercises, which are added to the points from the passed exam. The points earned from exercises can raise the final grade by a maximum of 0.75.