Academic year 2023/2024 |
Supervisor: | prof. Ing. Radomil Matoušek, Ph.D. | |||
Supervising institute: | ÚAI | |||
Teaching language: | Czech | |||
Aims of the course unit: | ||||
The course objective is to make students familiar with basic resources of artificial intelligence, potential and adequacy of their use in engineering problems solving. | ||||
Learning outcomes and competences: | ||||
Understanding of basic methods of artificial intelligence and ability of their implementation. | ||||
Prerequisites: | ||||
Knowledge of algorithmization, programming and the basics of mathematical logic and probability theory are assumed. | ||||
Course contents: | ||||
The course introduces basic approaches to artificial intelligence algorithms and classical methods used in the field. Main emphasis is given to automated formulas proves, knowledge representation and problem solving. Practical use of the methods is demonstrated on solving simple engineering problems. | ||||
Teaching methods and criteria: | ||||
The course is taught through lectures explaining the basic principles and theory of the discipline. Exercises are focused on practical topics presented in lectures. | ||||
Assesment methods and criteria linked to learning outcomes: | ||||
Course-unit credit requirements: passing partial tests and submitting a functional software project which uses implementation of selected AI method. Student can obtain 100 marks, 40 marks during seminars (20 for tests and 20 for project; he needs at least 20), 60 marks during exam (he needs at least 30). | ||||
Controlled participation in lessons: | ||||
The attendance at lectures is recommended, at seminars it is obligatory. Education runs according to week schedules. The form of compensation of missed seminars is fully in the competence of a tutor. | ||||
Type of course unit: | ||||
Guided consultation in combined form of studies | 1 × 17 hrs. | compulsory | ||
Guided consultation | 1 × 35 hrs. | optionally | ||
Course curriculum: | ||||
Guided consultation in combined form of studies | 1. Introduction to artificial intelligence. |
|||
Guided consultation | 1. Introductory motivational examples. |
|||
Literature - fundamental: | ||||
1. Kim W.Tracy, Peter Bouthoorn: Object-oriented Artificial Intelligence Using C++ | ||||
2. Edward A. Bender: Mathematical Methods in Artificial Intelligence | ||||
Literature - recommended: | ||||
1. F.Zbořil a kol.: Umělá inteligence (skriptum VUT) |
The study programmes with the given course: | |||||||||
Programme | Study form | Branch | Spec. | Final classification | Course-unit credits | Obligation | Level | Year | Semester |
N-AIŘ-K | combined study | --- no specialisation | -- | Cr,Ex | 4 | Compulsory | 2 | 1 | S |
Faculty of Mechanical Engineering
Brno University of Technology
Technická 2896/2
616 69 Brno
Czech Republic
+420 541 14n nnn
+420 726 81n nnn – GSM Telef. O2
+420 604 07n nnn – GSM T-mobile
Operator: nnnn = 1111