Second Cycle Degree/Two Year Master in Artificial intelligence

Exams and average marks

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
COMPLEX SYSTEMS & NETWORK SCIENCE 1 25
MACHINE LEARNING FOR COMPUTER VISION 23 27
ETHICS IN ARTIFICIAL INTELLIGENCE 100 29
COMBINATORIAL DECISION MAKING AND OPTIMIZATION 135 28
MULTIMEDIA DATA MANAGEMENT M 1 28
AUTONOMOUS AND ADAPTIVE SYSTEMS M 14 27
BIG DATA ANALYTICS AND TEXT MINING 39 29
BLOCKCHAIN AND CRYPTOCURRENCIES 13 26
CYBERSECURITY 9 28
CRYPTOGRAPHY 9 27
SOCIAL NETWORK ANALYSIS 85 28
COGNITION AND NEUROSCIENCE 127 27
SCALABLE AND RELIABLE SERVICES M 3 30
MACHINE LEARNING AND DEEP LEARNING I.C. 128 28
ARTIFICIAL INTELLIGENCE AND ROBOTICS 8 28
DATA MINING, TEXT MINING AND BIG DATA ANALYTICS 9 29
DISTRIBUTED AUTONOMOUS SYSTEMS M 4 28
INTERNET OF THINGS 11 28
NATURAL LANGUAGE PROCESSING 124 27
KNOWLEDGE ENGINEERING 5 28
LANGUAGES AND ALGORITHMS FOR ARTIFICIAL INTELLIGENCE I.C. 89 27
LANGUAGES AND ALGORITHMS FOR ARTIFICIAL INTELLIGENCE 52 25
DEEP LEARNING 3 30
USER EXPERIENCE DESIGN 7 26
INTRODUCTION TO LANGUAGES FOR ARTIFICIAL INTELLIGENCE 2 27
LABORATORY OF BUSINESS PLAN 1 28
MULTI-AGENT SYSTEMS 14 29
IMAGE PROCESSING AND COMPUTER VISION 125 25
ARTIFICIAL INTELLIGENCE IN INDUSTRY 108 29
ARCHITECTURES AND PLATFORMS FOR ARTIFICIAL INTELLIGENCE 14 27
MACHINE LEARNING AND DATA MINING 10 25
STATISTICAL AND MATHEMATICAL METHODS FOR ARTIFICIAL INTELLIGENCE 132 27
INTRODUCTION TO COMPUTABILITY AND COMPLEXITY 1 21
COMPUTATIONAL ETHICS 3 29
MACHINE LEARNING AND DEEP LEARNING I.C. 7 26
FUNDAMENTALS OF ARTIFICIAL INTELLIGENCE AND KNOWLEDGE REPRESENTATION 141 27