Study guides
Timetables
Timetable
Table of credits for each course
| |
Basic training |
Compulsory |
Optional |
Final Project |
| 1st year |
48 |
12 |
|
|
| 2nd year |
12 |
48 |
|
|
| 3rd year |
|
48 |
12 |
|
| 4rd year |
|
12 |
36 |
12 |
| Total |
60 |
120 |
48 |
12 |
Basic and compulsory training
| 1st year |
2nd year |
|
1st semester
- Fundamentals of Programming I
- Fundamentals of Mathematics I
- Introduction to AI
- Fundamentals of Computing
- Computational Logics
2nd semester
- Fundamentals of Programming II
- Probability and Statistics
- Data Engineering
- Fundamentals of Mathematics II
|
1st semester
- Problem Solving
- Fundamentals of Machine Learning
- Knowledge Representation
- Fundamentals of Artificial Vision
- Data Management
2nd semester
- Cognitive Processes
- Neural Networks and Deep Learning
- Graph and Network Analysis
- Fundamentals of Natural Language
- Cloud Computing
|
| 3rd year |
4th year |
|
1st semester
- Parallel Programming
- Regulation of AI
- Ethics
- Intelligent Robots
- Synthesis Project I
2nd semester
- Reinforcement Learning
- The Social Impact of AI
- Social and Human Interaction with AI
- Synthesis Project II
|
1st semester
- Autonomous Agents
- Mind and Brain
1st or 2nd semester
- Bachelor's Degree Final Project
|
Optional subjects
All optional subjects are worth 6 credits except for Work Placement, which is worth 12 credits.
| 3rd and 4th years |
|
- Software Engineering
- Data Security and Privacy
- Visual Recognition
- Advanced Artificial Vision
- Learning and Natural Language Processing
- Multi-agent Systems
- Advanced Machine Learning
- Autonomous Navigation
- IoT Systems
- Applications and Challenges of AI
- Current Trends in Machine Learning
- Innovation and Entrepreneurship
- Game Theory
- Computing Acceleration in AI
- Work Placement
|