Courses for Cybersecurity
The two-year master's programme in Cybersecurity consists of three semesters of courses and one final semester dedicated to the master's degree project. Each semester consists of approximately 30 ECTS credits. The courses presented on this page apply to studies starting in autumn 2024.
Year 1
The mandatory courses AK2030 Theory and Methodology of Science and DA2215 Theory of Science and Scientific methods in Cybersecurity can be taken at any period during the programme.
At least 30 credits of the conditionally elective courses must be taken.
Mandatory courses
- Theory and Methodology of Science (Natural and Technological Science) (AK2030) 4.5 credits
- Theory of Science and Scientific methods in Cybersecurity (DA2215) 3.0 credits
- The Cybersecurity Engineer's Role in Society (DD2303) 2.0 credits
- Cybersecurity Overview (DD2391) 7.5 credits
- Cybersecurity in a Socio-Technical Context (DD2510) 7.5 credits
- Applied Cryptography (DD2520) 7.5 credits
- Ethical Hacking (EN2720) 7.5 credits
Conditionally elective courses
- Foundations of Cryptography (DD2448) 7.5 credits
- Privacy Enhancing Technologies (DD2496) 7.5 credits
- Project course in System Security (DD2497) 7.5 credits
- Language-Based Security (DD2525) 7.5 credits
- Cyber-Physical Security in Time-Critical Systems (EL2850) 7.5 credits
- Networked Systems Security (EP2500) 7.5 credits
- Advanced Networked Systems Security (EP2510) 7.5 credits
- Building Networked Systems Security (EP2520) 7.5 credits
- Digital forensics and incident response (EP2780) 7.5 credits
- Security Analysis of Large-Scale Computer Systems (EP2790) 7.5 credits
- Design of Fault-tolerant Systems (ID2218) 7.5 credits
- Hardware Security (IL1333) 7.5 credits
Recommended courses
- Foundations of Machine Learning (DD1420) 7.5 credits
- Deep Learning, Advanced Course (DD2412) 6.0 credits
- Machine Learning (DD2421) 7.5 credits
- Deep Learning in Data Science (DD2424) 7.5 credits
- Machine Learning, Advanced Course (DD2434) 7.5 credits
- Artificial Neural Networks and Deep Architectures (DD2437) 7.5 credits
- Advanced Algorithms (DD2440) 6.0 credits
- Parallel and Distributed Computing (DD2443) 7.5 credits
- Statistical Methods in Applied Computer Science (DD2447) 6.0 credits
- Interaction Design Methods (DH2628) 7.5 credits
- Communication and Control in Electric Power Systems (EG2130) 7.5 credits
- Reinforcement Learning (EL2805) 7.5 credits
Year 2
At least 30 credits of the conditionally elective courses must be taken.
Mandatory courses
- Theory and Methodology of Science (Natural and Technological Science) (AK2030) 4.5 credits
- Theory of Science and Scientific methods in Cybersecurity (DA2215) 3.0 credits
- Degree Project in Computer Science and Engineering, specialising in Cybersecurity (DA237X) 30.0 credits
- The Cybersecurity Engineer's Role in Society (DD2303) 2.0 credits
- Cybersecurity in a Socio-Technical Context (DD2510) 7.5 credits
Conditionally elective courses
- Foundations of Cryptography (DD2448) 7.5 credits
- Software Safety and Security (DD2460) 7.5 credits
- Automated Software Testing and DevOps (DD2482) 7.5 credits
- Privacy Enhancing Technologies (DD2496) 7.5 credits
- Project course in System Security (DD2497) 7.5 credits
- Language-Based Security (DD2525) 7.5 credits
- Cyber-Physical Security in Time-Critical Systems (EL2850) 7.5 credits
- Networked Systems Security (EP2500) 7.5 credits
- Advanced Networked Systems Security (EP2510) 7.5 credits
- Building Networked Systems Security (EP2520) 7.5 credits
- Digital forensics and incident response (EP2780) 7.5 credits
- Security Analysis of Large-Scale Computer Systems (EP2790) 7.5 credits
- Design of Fault-tolerant Systems (ID2218) 7.5 credits
- Hardware Security (IL1333) 7.5 credits
Recommended courses
- Foundations of Machine Learning (DD1420) 7.5 credits
- Deep Learning, Advanced Course (DD2412) 6.0 credits
- Machine Learning (DD2421) 7.5 credits
- Deep Learning in Data Science (DD2424) 7.5 credits
- Machine Learning, Advanced Course (DD2434) 7.5 credits
- Artificial Neural Networks and Deep Architectures (DD2437) 7.5 credits
- Advanced Algorithms (DD2440) 6.0 credits
- Parallel and Distributed Computing (DD2443) 7.5 credits
- Statistical Methods in Applied Computer Science (DD2447) 6.0 credits
- Dependable Autonomous Systems (DD2528) 7.5 credits
- Interaction Design Methods (DH2628) 7.5 credits
- Communication and Control in Electric Power Systems (EG2130) 7.5 credits
- Reinforcement Learning (EL2805) 7.5 credits