Course detail

Artificial Intelligence and Machine Learning

FIT-CZV-SUIAcad. year: 2026/2027

Not applicable.

Language of instruction

Czech

Number of ECTS credits

5

Assignment to study programme types

lifelong learning

Mode of study

Not applicable.

Guarantor

Ing. Michal Hradiš, Ph.D.

Department

Department of Computer Graphics and Multimedia (UPGM)

Entry knowledge

Not applicable.

Rules for evaluation and completion of the course

Not applicable.

Aims

Not applicable.

Study aids

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

Not applicable.

Recommended reading

C. Bishop: Pattern Recognition and Machine Learning, Springer, 2006
Ertel, W.: Introduction to Artificial Intelligence, Springer, second edition 2017, ISSN 1863-7310
Goodfellow, I., Bengio, Y., Courville, A.: Deep Learning. MIT Press, 2016.
Materiály k přednáškám dostupné v Moodlu
Russel,S., Norvig,P.: Artificial Intelligence, Prentice-Hall, Inc., third edition 2010, ISBN 0-13-604259-7

Classification of course in study plans

  • Programme CZV3-Cyber Lifelong learning - long-term course 2 year of study, winter semester, elective

Type of course unit

 

Individual preparation - working on the assigned tasks

30 hours, optionally

Teacher / Lecturer

Ing. Michal Hradiš, Ph.D.

Individual preparation for an ending of the course

20 hours, optionally

Teacher / Lecturer

Ing. Michal Hradiš, Ph.D.

Lecture

20 hours, optionally

Teacher / Lecturer

Ing. Michal Hradiš, Ph.D.

Guided consultation in combined form of studies

10 hours, optionally

Teacher / Lecturer

Ing. Michal Hradiš, Ph.D.

Individual preparation for a project work

20 hours, optionally

Teacher / Lecturer

Ing. Michal Hradiš, Ph.D.

Individual preparation - study of technical texts

30 hours, optionally

Teacher / Lecturer

Ing. Michal Hradiš, Ph.D.