Artificial Intelligence 420-IS1-3SZI

Study profile: general academic
Study form: full-time
Type of course: obligatory
Scientific domain: exact and natural sciences; discipline: computer science
Year/semester: 3/6
Lecture: 30h, Laboratory: 15h, Project: 15h
Didactic methods: lecture, laboratory, realization of a project and preparation of a report, individual consulting with teachers.
ECTS: 4
Balance of a student's labour input:
Participation in classes:
- lecture 30h
- laboratory 15h
- project 15h
Preparation to classes:
- Preparation to classes: lecture - 3h, lab - 10h, project - 7h
- Getting acquainted with the literature: 10h
- Reports and other: 10h
- Preparation to the exam: 10h
Duration of the exam: 2h
Individual consulting with teachers: 3h
Activities requiring of a direct participation of the teacher: 65h, 2 ECTS
Activities not requiring of a direct participation of the teacher: 50h, 2 ECTS

Prerequisites (description)

A student is assumed to have some knowledge of the theory and the practice of such research fields as logic, set theory, probability theory, statistics, mathematical analysis, discrete mathematics, algorithms and data structures, and to be familiar with programming.

Course coordinators

Anna Gomolińska

Type of course

obligatory courses

Mode

(in Polish) w sali

Learning outcomes

Knowledge :
knows elementary notions, properties, and methods used in the main research fields of artificial intelligence - KA6_WG11.
Skills:
- can describe problems expressed in natural language using an artificial intelligence terminology - KA6_UW14;
- can solve a project task, present its solution, and draw conclusions - KA6_UK3;
- can collaborate with others on the realization of a project if needed - KA6_UO2;
- can follow the development of the artificial intelligence methods and technologies - KA6_UU1.
Social competence:
is ready for following of the ethical and legal rules concerning the development and the usage of programmes and systems of artificial intelligence - KA6_KR.

Assessment criteria

The general form of the credit: an exam

Bibliography

1. M. Flasiński, Introduction to Artificial Intelligence, Springer Verlag, Switzerland 2016.
2. S.J. Russell, P. Norvig, Artificial Intelligence: A Modern Approach, 3rd Ed., Pearson, 2014.
3. L. Rutkowski, Computational Intelligence. Methods and Techniques, Springer-Verlag, Berlin Heidelberg 2008.

Additional information

Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system:

Description of 420-IS1-3SZI in USOSweb