The following courses are part of study year two.

The course application codes and study periods are valid for the academic year 2021/2022. For other academic years, different application codes and study periods may apply.

General courses

Courses that run in periods 1 and 2 of Year 2 can potentially be taken in period 1 and period 2 of Year 1 if its leads to a manageable workload for the student.

Apart from the mandatory and conditionally elective course requirements the student is free to choose from all the second cycle and language courses given at KTH to take his/her number of completed course credits to 90 ECTS. First cycle courses may be taken (though we prefer if students take second-cycle courses) but no more than 30 ECTS points can be counted towards graduation. recommended courses is for  those who would like to extend their competency and knowledge in Computer Science and Software Engineering. A final degree project must also be completed.

Mandatory courses

Course code and name Appl.code Scope P1 P2 P3 P4
DD2301 Program Integrating Course in Machine Learning 50684 3.0 hp 0.5 0.5
DA233X Degree Project in Computer Science and Engineering, specializing in Machine Learning, Second Cycle 30.0 hp

Choose among the conditionally elective courses, so that the following conditions are fulfilled:

    - at least 6 courses from Application Domains + Theory, and
    - at least 2 courses from Application Domains, and also
    - at least 2 courses from Theory.

Examples of possible combinations of courses:

    - at least 2 courses from Application Domains, and at least 4 courses from Theory,
    - at least 3 courses from Application Domains, and at least 3 courses from Theory,
    - at least 4 courses from Application Domains, and at least 2 courses from Theory.

Conditionally elective courses

Course code and name Appl.code Scope P1 P2 P3 P4
DD2411 Research project in Robotics, Perception and Learning Included in Application Domain, Robotics 60503 15.0 hp 4.0 3.5
DD2257 Visualization Included in Application Domain Visualization 7.5 hp
DD2410 Introduction to Robotics Included in Application Domain, Robotics 7.5 hp
DD2412 Deep Learning, Advanced Course Included in Theory, Machine Learning 6.0 hp
DD2419 Project Course in Robotics and Autonomous Systems Included in Application Domain, Robotics 9.0 hp
DD2420 Probabilistic Graphical Models Included in Theory, Machine Learning 7.5 hp
DD2423 Image Analysis and Computer Vision Included in Application Domain Computer Vision 7.5 hp
DD2430 Project Course in Data Science Included in Application Domain 7.5 hp
DD2435 Mathematical Modelling of Biological Systems Included in Application Domain, Computational Biology 9.0 hp
DD2437 Artificial Neural Networks and Deep Architectures Included in Theory, Machine Learning 7.5 hp
DD2438 Artificial Intelligence and Multi Agent Systems Included in Application Domain, Robotics 15.0 hp
DD2447 Statistical Methods in Applied Computer Science Included in Theory, Statistics & Probability 6.0 hp
EL2320 Applied Estimation Included in Theory, Mathematics 7.5 hp
EL2805 Reinforcement Learning Included in Theory, Machine Learning 7.5 hp
EQ2425 Analysis and Search of Visual Data Included in Application Domain Computer Vision 7.5 hp
ID2222 Data Mining Included in Theory, Machine Learning 7.5 hp
ID2223 Scalable Machine Learning and Deep Learning Included in Theory, Machine Learning 7.5 hp
SF1811 Optimization Included in Theory, Mathematics 6.0 hp
SF2930 Regression Analysis Included in Theory, Statistics & Probability 7.5 hp
SF2940 Probability Theory Included in Theory, Statistics & Probability 7.5 hp

Recommended courses

Course code and name Appl.code Scope P1 P2 P3 P4
DD1388 Program System Construction Using C++ 7.5 hp
DD2352 Algorithms and Complexity 7.5 hp
DD2395 Computer Security 6.0 hp
DD2448 Foundations of Cryptography 7.5 hp
DH2642 Interaction Programming and the Dynamic Web 7.5 hp
ID2213 Logic Programming 7.5 hp
ID2221 Data-Intensive Computing 7.5 hp
SF2568 Parallel Computations for Large- Scale Problems 7.5 hp