| Course title | Introduction to Artificial Intelligence |
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| Course code | KMI/UUI |
| Organizational form of instruction | Lecture |
| Level of course | unspecified |
| Year of study | not specified |
| Semester | Winter |
| Number of ECTS credits | 4 |
| Language of instruction | Czech |
| Status of course | unspecified |
| Form of instruction | unspecified |
| Work placements | This is not an internship |
| Recommended optional programme components | None |
| Lecturer(s) |
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| Course content |
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1. General introduction to artificial intelligence - technology overview 2. Basic concepts of machine learning 3. Machine learning - overview of algorithms 3. Neural networks - basic concepts 4. Other types of neural networks, convolutional neural networks 5. Graph neural networks, Node2Vec 6. Feedback learning 7. Word processing, Word2Vec 8. Image recognition 9. Other applications of neural networks 10. Technology Agents 11. Selected applications in economics
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| Learning activities and teaching methods |
Monologic (reading, lecture, briefing), Demonstration, Work with multi-media resources (texts, internet, IT technologies)
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| Learning outcomes |
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Identification and characterization of artificial intelligence, the formulation of the background and basic problems of the field of artificial intelligence. The concept of an intelligent system, modeling of intelligent systems, the use of simulation in system design, working with uncertain and incomplete information, the foundations of soft computing, agent and multiagent architectures, learning adaptive systems, reinforcement learning, planning applications. The main focus is the use of neural networks in these technologies.
By completing the course students acquire basic overview of the issues covered in artificial intelligence as well as methods for their solution. Emphasis is focused on developing the student's ability to solve practical problems with the use of neural networks. |
| Prerequisites |
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Subjects MATI, MATII. Knowledge of programming in a programming language, e.g. Python
KMI/CM1 ----- or ----- KMI/KMATI ----- or ----- KMI/MATI ----- or ----- KMI/M1 and KMI/CM2 ----- or ----- KMI/KMATA ----- or ----- KMI/KMIIA ----- or ----- KMI/KMTII ----- or ----- KMI/MAIIA ----- or ----- KMI/MATIA ----- or ----- KMI/MATII ----- or ----- KMI/M1A ----- or ----- KMI/M2 ----- or ----- KMI/M2A ----- or ----- KMI/YMAII ----- or ----- KMI/YMATI |
| Assessment methods and criteria |
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Test
Requirements on students: Processing of assignments during the semester Pass the final written test - - solving the assigned task |
| Recommended literature |
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| Study plans that include the course |
| Faculty | Study plan (Version) | Category of Branch/Specialization | Recommended semester |
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