Fundamentals of Artificial Intelligence (5cr)

Objectives (course unit)

The student knows the key concepts, methods and algorithms related to artificial intelligence.

The student is able to train artificial intelligence models with their own data.

The student learns to evaluate the performance of the models using various evaluation methods.

The student learns to use the artificial intelligence model they have taught in practice with new data and understands the results provided by the model.

Content (course unit)

Fundamentals and key methods of data and artificial intelligence in the Python programming language. Key concepts and methods, classic machine learning algorithms and various applications.

Assessment criteria, satisfactory (1-2) (course unit)

The student knows the basics and most important concepts of artificial intelligence. The student is able to train an artificial intelligence model with data, either guided or through examples.

Assessment criteria, good (3-4) (course unit)

The student knows the basics of artificial intelligence, the most important concepts and methods. The student trains an artificial intelligence model with their own data. The student knows the methods used in evaluating the model.

Assessment criteria, excellent (5) (course unit)

The student knows the basics of artificial intelligence, the most important concepts and methods. The student trains an artificial intelligence model with their own data. The student also knows alternative algorithms that can be utilized. The student knows the methods used in model evaluation and is able to evaluate the mutual performance of different models.

Assessment scale

0-5