Skip to main content
Till KTH:s startsida

Study year 1

The following courses are part of study year one.

The course application codes and study periods are valid for the academic year 2025/2026. 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 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 nameAppl.codeScopeP1P2P3P4
DD1420 Foundations of Machine LearningOverlaps with DD2421503127.5 credits7.5
DD2380 Artificial IntelligenceOverlaps with ID1214 at CINTE503746.0 credits6.0
DA2205 Introduction to the Philosophy of Science and Research Methodology503767.5 credits3.04.5
DD2301 Program Integrating Course in Machine Learning503773.0 credits0.50.50.50.5
DD2434 Machine Learning, Advanced Course503257.5 credits7.5

Students must complete the mandatory courses (A.1.1) and conditionally elective courses. The conditionally elected courses are gouped into two sets; Application Domain (A.1.3), and Theory (A.1.4). A student must complete:

- at least 6 courses from Application Domain and Theory,

with the constraints that

- at least 2 of the 6 courses are from the Theory courses and
- at least 2 of the 6 courses are from the Application Domain courses.

Explicitly this means that students to graduate must have either completed:

- 2 courses from Application Domain and 4 courses from Theory,
- 3 courses from Application Domain and3 courses from Theory,
- 4 courses from Application Domain and 2 courses from Theory.

Apart from the mandatory and conditionally elective courses requirements the student is free to choose from all the second cycle and language courses given at KTH to take the number of completed course credits of 90 ECTS. First cycle courses may be taken (though we prefer if students take scond-cycle courses) but no more that 30 ECTS points can be counted towards graduation. Courses that are not allowed as elective are hobby courses like cooking, bar-tending etc. In section A.1.5 we list a set of recommended courses that students could take especially those who would like to extend theid competency and knowledge in Computer Science and Software Engineering. A final degree project (A.1.2) must also be completed.

Students who in a previous degree have read a course correspinding to DD1420, DD2380 or DD2434 may apply to read a replacement course instead. The application is submitted to the master coordinator who, after reviewing the previously read course, gives persmission for the student to take a replacement cours from the set of conditionally elective or recommended courses. The course replacement course, if it is a conditionally elective course, will not count towards one of the 6 conditionally elective course requirements. 

Student who completed their first three years of study at KTH within the programme CINTE, who have read ID1214 Artificial Intelligence and Applications, can apply to read a replacement course. Contact the master coordinator according to the instruction above.

Conditionally elective courses

Course code and nameAppl.codeScopeP1P2P3P4
DD2257 VisualizationIncluded in Application Domain Visualization503737.5 credits7.5
DD2410 Introduction to RoboticsIncluded in Application Domain, Robotics 503607.5 credits7.5
DT2470 Music InformaticsIncluded in Application Domain, Sound503687.5 credits7.5
EQ2425 Analysis and Search of Visual DataIncluded in Application Domain Computer Vision503627.5 credits7.5
SF2940 Probability TheoryIncluded in Theory, Statistics & Probability503097.5 credits7.5
DD2435 Mathematical Modelling of Biological SystemsIncluded in Application Domain, Computational Biology503589.0 credits6.03.0
DD2423 Image Analysis and Computer VisionIncluded in Application Domain Computer Vision503537.5 credits7.5
DD2447 Statistical Methods in Applied Computer ScienceIncluded in Theory, Statistics & Probability (may not be combined with DD2420)520386.0 credits6.0
EL2320 Applied EstimationIncluded in Theory, Mathematics503757.5 credits7.5
EL2805 Reinforcement LearningIncluded in Theory, Machine Learning511857.5 credits7.5
ID2222 Data MiningIncluded in Theory, Machine Learning503717.5 credits7.5
ID2223 Scalable Machine Learning and Deep LearningIncluded in Theory, Machine Learning503727.5 credits7.5
SF1811 OptimizationIncluded in Theory, Mathematics502856.0 credits6.0
DD2420 Probabilistic Graphical ModelsIncluded in Theory, Statistics & Probability (may not be combined with DD2447)602717.5 credits7.5
DD2437 Artificial Neural Networks and Deep ArchitecturesIncluded in Theory, Machine Learning609697.5 credits7.5
DT2112 Speech TechnologyIncluded in Application Domain, Language Processing; Speech & Text602487.5 credits7.5
EL2810 Machine Learning TheoryIncluded in Theory, Machine Learning 603047.5 credits7.5
SF2930 Regression AnalysisIncluded in Theory, Statistics & Probability602377.5 credits7.5
DD2402 Advanced Individual Course in Computational BiologyIncluded in Application Domain, Computational Biology603106.0 credits3.03.0
DD2411 Research project in Robotics, Perception and LearningIncluded in Application Domain, Robotics6032515.0 credits4.03.5
DD2419 Project Course in Robotics and Autonomous SystemsIncluded in Application Domain, Robotics603189.0 credits4.54.5
DD2438 Artificial Intelligence and Multi Agent SystemsIncluded in Application Domain, Robotic6024715.0 credits7.08.0
DD2477 Search Engines and Information Retrieval SystemsIncluded in Application Domain Databases/Information Retrieval602517.5 credits4.53.0
DD2401 NeuroscienceIncluded in Application Domain, Computational Biology614287.5 credits7.5
DD2417 Language EngineeringIncluded in Application Domain Language Processing; Speech & Text602467.5 credits7.5
DD2424 Deep Learning in Data ScienceIncluded in Application Domain Computer Vision602287.5 credits7.5
DT2119 Speech and Speaker RecognitionIncluded in Application Domain, Language Processing; Speech & Text602527.5 credits7.5
EQ2341 Pattern Recognition and Machine LearningIncluded in Theory, Machine Learning603237.5 credits7.5
SF2943 Time Series AnalysisIncluded in Theory, Statistics & Probability603267.5 credits7.5

Recommended courses

Course code and nameAppl.codeScopeP1P2P3P4
DD2395 Computer Security503016.0 credits6.0
ID2221 Data-Intensive Computing503707.5 credits7.5
IK2215 Advanced Internetworking504567.5 credits7.5
IK2227 Network Systems with Edge or Cloud Datacenters604137.5 credits7.5
DD1388 Program System Construction Using C++603147.5 credits4.03.5
DD2352 Algorithms and Complexity603197.5 credits3.04.5
DH2642 Interaction Programming and the Dynamic Web602897.5 credits4.53.0
DD2448 Foundations of Cryptography602337.5 credits7.5
IK2221 Networked Systems for Machine Learning600087.5 credits7.5