List of programme's course units, number of exams (i.e. how many times the exam was taken in a year) and average marks
The data refer to last year. A course unit may include modules, subgroups, integrated exams. Proficiency tests are not included in the list.
| Course unit | Number of times exam was taken | Average mark |
|---|---|---|
| CRYPTOGRAPHY | 1 | 25 |
| STATISTICAL AND MATHEMATICAL METHODS FOR ARTIFICIAL INTELLIGENCE | 95 | 26 |
| COMPLEX SYSTEMS & NETWORK SCIENCE | 4 | 30 |
| DEEP LEARNING | 1 | 18 |
| DATA MINING, TEXT MINING AND BIG DATA ANALYTICS | 55 | 29 |
| MACHINE LEARNING FOR COMPUTER VISION | 54 | 27 |
| DISTRIBUTED AUTONOMOUS SYSTEMS M | 4 | 26 |
| SOCIAL NETWORK ANALYSIS | 63 | 28 |
| USER EXPERIENCE DESIGN | 12 | 26 |
| COMBINATORIAL DECISION MAKING AND OPTIMIZATION | 93 | 28 |
| MACHINE LEARNING AND DEEP LEARNING I.C. | 26 | 27 |
| MULTIMEDIA DATA MANAGEMENT M | 3 | 28 |
| CYBERSECURITY | 15 | 27 |
| BLOCKCHAIN AND CRYPTOCURRENCIES | 10 | 29 |
| MULTI-AGENT SYSTEMS | 11 | 29 |
| ETHICS IN ARTIFICIAL INTELLIGENCE | 82 | 29 |
| MACHINE LEARNING AND DEEP LEARNING I.C. | 65 | 28 |
| KNOWLEDGE ENGINEERING | 8 | 25 |
| IMAGE PROCESSING AND COMPUTER VISION | 83 | 25 |
| ARCHITECTURES AND PLATFORMS FOR ARTIFICIAL INTELLIGENCE | 27 | 29 |
| MACHINE LEARNING AND DATA MINING | 2 | 19 |
| COGNITION AND NEUROSCIENCE | 139 | 27 |
| FUNDAMENTALS OF ARTIFICIAL INTELLIGENCE AND KNOWLEDGE REPRESENTATION | 124 | 28 |
| ARTIFICIAL INTELLIGENCE AND ROBOTICS | 8 | 29 |
| LANGUAGES AND ALGORITHMS FOR ARTIFICIAL INTELLIGENCE | 115 | 26 |
| BIG DATA ANALYTICS AND TEXT MINING | 1 | 30 |
| EXPERT SYSTEMS | 2 | 24 |
| INTRODUCTION TO COMPUTABILITY AND COMPLEXITY | 1 | 18 |
| AUTONOMOUS AND ADAPTIVE SYSTEMS M | 18 | 25 |
| NATURAL LANGUAGE PROCESSING | 122 | 28 |
| INTERNET OF THINGS | 6 | 29 |
| ARTIFICIAL INTELLIGENCE IN INDUSTRY | 110 | 29 |
| SCALABLE AND RELIABLE SERVICES M | 3 | 28 |
