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
- Cognitive Processes
- Computational Logics
2nd semester
- Fundamentals of Programming II
- Fundamentals of Computing
- Probability and Statistics
- Data Engineering
- Fundamentals of Mathematics II
|
1st semester
- Problem Resolution
- Automatic Learning Fundamentals
- Ethics
- Mind and Brain I
- Fundamentals of Computer Vision
2nd semester
- Representation of Knowledge
- Neural Networks and Profound Learning
- Analysis of Graphs and Networks
- Fundamentals of Natural Language
- Synthesis Project I
|
| 3r curs |
4t curs |
|
1st semester
- Project Management
- AI Regulation
- Data Management
- Intelligent Robots
2nd semester
- Distributed Programming
- Social Innovation
- Autonomous Agents
- Synthesis Project II
|
- AI Challenges and Applications I
- Social Interaction
- Bachelo's Degree Final Project
|
Optional subjects
All optional subjects are worth 6 credits except for the subject External Work Placement, which is worth 12 credits.
| 3rd and 4th years |
4th year |
- Logic Formalisms
- Parellel Programming
- Software Engineering
- Data Security and Privacy
- Mind and Brain II
- Vision and Learning
- 3D Vision and Movement Analysis
- Natural Language Learning and Processing
- Applications of Natural Language Processing
- Multi-agent Systems
- Paradigms of Automatic Learning
- Advanced Automatic Learning
- Sequential Model Learning
- Self-Navigation
- IoT Systems
- AI Challenges and Applications II
- AI Challenges and Applications III
- Innovation and Entrepreneurship
- Game Theory
- AI Computing Acceleration
|
|