Offered teachings

This page lists the teachings offered within the master programme in computer science, together with their classifications.

Namely, here you will find the the teachings characterising each computer science area (such sets of teachings are called recommended completion pathways, RPC, in the regulation) as well as those in the class of "related teachings".

Teachings in Recommended Completion Pathways

You need to choose your RPCs in order to comply with step 1 of our guidelines and to design a valid study plan.

RPC in Algorithms (30 credits)

1. Advanced Algorithms

2. Computational Complexity

3. Cryptography

4. Graph Theory

5. Network Algorithms

RPC in Artificial Intelligence (36 credits)

1. Advanced Machine Learning

2. Big Data Computing

3. Computer Vision

4. Deep Learning and Applied Artificial Intelligence

5. Formal Methods for AI-Based Systems Engineering

6. Natural Language Processing

RPC in Computational Models for Systems Design (30 credits)

1. Automatic Verification of Intelligent Systems

2. Concurrent Systems

3. Formal Methods for AI-Based Systems Engineering 

4. Mathematical Logic for Computer Science 

5. Models of Computation

RPC in Data Science (30 credits)

1. Advanced Machine Learning

2. Big Data Computing

3. Cloud Computing

4. Data and Network Security

5. Foundations of Data Science

RPC in Multimedia Computing and Interaction (48 credits)

1. Advanced Machine Learning

2. Advanced Software Engineering

3. Biometric Systems

4. Computer Vision

5. Deep Learning and Applied Artificial Intelligence

6. Human-Computer Interaction on The Web

7. Multimodal Interaction

8. Natural Language Processing

RPC in Networks (24 credits)

1. Autonomous Networking

2. Computer Network Performance

3. Internet of Things

4. Network Algorithms

RPC in Security (36 credits)

1. Biometric Systems

2. Blockchain and Distributed Ledger Technologies

3. Cryptography

4. Data and Network Security

5. Practical Network Defense

6. Security in Software Applications

RPC in Software Engineering (48 credits)

1. Advanced Algorithms

2. Advanced Software Engineering

3. Automatic Verification of Intelligent Systems

4. Blockchain and Distributed Ledger Technologies

5. Concurrent Systems

6. Distributed Systems

7. Formal Methods for AI-Based Systems Engineering

8. Security in Software Applications

RPC in Systems (24 credits)

1. Advanced Architectures

2. Cloud Computing

3. Concurrent Systems

4. Distributed Systems

Related teachings

You need to select related teachings in order to comply with step 2 of our guidelines and to design a valid study plan.

1. Advanced Algorithms

2. Advanced Architectures

3. Advanced Machine Learning

4. Advanced Software Engineering

5. Automatic Verification of Intelligent Systems

6. Autonomous Networking

7. Big Data Computing

8. Biometric Systems

9. Blockchain and Distributed Ledger Technologies

10. Cloud Computing

11. Computational Complexity

12. Computer Network Performance

13. Computer Vision

14. Concurrent Systems

15. Cryptography

16. Data and Network Security

17. Data-Driven Modeling of Complex Systems 

18. Deep Learning and Applied Artificial Intelligence

19. Distributed Systems

20. Ethical Hacking 

21. Formal Methods for AI-Based Systems Engineering

22. Foundations of Data Science 

23. Graph Theory

24. Human-Computer Interaction On The Web

25. Internet of Things

26. Mathematical Logic For Computer Science

27. Methods in Computer Science Education: Analysis

28. Methods in Computer Science Education: Design

29. Models of Computation

30. Multimodal Interaction

31. Natural Language Processing

32. Network Algorithms

33. Practical Network Defense

34. Security in Software Applications

35. Topics in Physics