The following courses are part of study year one.
The course application codes and study periods are valid for the academic year 2024/2025. 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 |
|---|---|---|---|---|---|---|
| DD1420 Foundations of Machine Learning | 7.5 credits | 7.5 | ||||
| DD2380 Artificial IntelligenceOverlaps with ID1214 at CINTE | 6.0 credits | 6.0 | ||||
| DA2205 Introduction to the Philosophy of Science and Research Methodology | 7.5 credits | 3.0 | 4.5 | |||
| DD2301 Program Integrating Course in Machine Learning | 3.0 credits | 0.5 | 0.5 | 0.5 | 0.5 | |
| DD2434 Machine Learning, Advanced Course | 7.5 credits | 7.5 |
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 name | Appl.code | Scope | P1 | P2 | P3 | P4 |
|---|---|---|---|---|---|---|
| DD2257 VisualizationIncluded in Application Domain Visualization | 7.5 credits | 7.5 | ||||
| DD2410 Introduction to RoboticsIncluded in Application Domain, Robotics | 7.5 credits | 7.5 | ||||
| DT2470 Music InformaticsIncluded in Application Domain, Sound | 7.5 credits | 7.5 | ||||
| EQ2425 Analysis and Search of Visual DataIncluded in Application Domain Computer Vision | 7.5 credits | 7.5 | ||||
| SF2940 Probability TheoryIncluded in Theory, Statistics & Probability | 7.5 credits | 7.5 | ||||
| DD2412 Deep Learning, Advanced CourseIncluded in Theory, Machine Learning | 6.0 credits | 3.0 | 3.0 | |||
| DD2435 Mathematical Modelling of Biological SystemsIncluded in Application Domain, Computational Biology | 9.0 credits | 6.0 | 3.0 | |||
| DD2423 Image Analysis and Computer VisionIncluded in Application Domain Computer Vision | 7.5 credits | 7.5 | ||||
| DD2447 Statistical Methods in Applied Computer ScienceIncluded in Theory, Statistics & Probability (may not be combined with DD2420) | 6.0 credits | 6.0 | ||||
| EL2320 Applied EstimationIncluded in Theory, Mathematics | 7.5 credits | 7.5 | ||||
| EL2805 Reinforcement LearningIncluded in Theory, Machine Learning | 7.5 credits | 7.5 | ||||
| ID2222 Data MiningIncluded in Theory, Machine Learning | 7.5 credits | 7.5 | ||||
| ID2223 Scalable Machine Learning and Deep LearningIncluded in Theory, Machine Learning | 7.5 credits | 7.5 | ||||
| SF1811 OptimizationIncluded in Theory, Mathematics | 6.0 credits | 6.0 | ||||
| DD2420 Probabilistic Graphical ModelsIncluded in Theory, Statistics & Probability (may not be combined with DD2447) | 60212 | 7.5 credits | 7.5 | |||
| DD2437 Artificial Neural Networks and Deep ArchitecturesIncluded in Theory, Machine Learning | 61667 | 7.5 credits | 7.5 | |||
| DT2112 Speech TechnologyIncluded in Application Domain, Language Processing; Speech & Text | 60210 | 7.5 credits | 7.5 | |||
| EL2810 Machine Learning TheoryIncluded in Theory, Machine Learning | 60482 | 7.5 credits | 7.5 | |||
| SF2930 Regression AnalysisIncluded in Theory, Statistics & Probability | 60214 | 7.5 credits | 7.5 | |||
| DD2402 Advanced Individual Course in Computational BiologyIncluded in Application Domain, Computational Biology | 60197 | 6.0 credits | 3.0 | 3.0 | ||
| DD2411 Research project in Robotics, Perception and LearningIncluded in Application Domain, Robotics | 60208 | 15.0 credits | 4.0 | 3.5 | ||
| DD2419 Project Course in Robotics and Autonomous SystemsIncluded in Application Domain, Robotics | 60204 | 9.0 credits | 4.5 | 4.5 | ||
| DD2438 Artificial Intelligence and Multi Agent SystemsIncluded in Application Domain, Robotic | 60209 | 15.0 credits | 7.0 | 8.0 | ||
| DD2477 Search Engines and Information Retrieval SystemsIncluded in Application Domain Databases/Information Retrieval | 60198 | 7.5 credits | 4.5 | 3.0 | ||
| DD2401 NeuroscienceIncluded in Application Domain, Computational Biology | 60206 | 7.5 credits | 7.5 | |||
| DD2417 Language EngineeringIncluded in Application Domain Language Processing; Speech & Text | 60194 | 7.5 credits | 7.5 | |||
| DD2424 Deep Learning in Data ScienceIncluded in Application Domain Computer Vision | 60207 | 7.5 credits | 7.5 | |||
| DT2119 Speech and Speaker RecognitionIncluded in Application Domain, Language Processing; Speech & Text | 60201 | 7.5 credits | 7.5 | |||
| EQ2341 Pattern Recognition and Machine LearningIncluded in Theory, Machine Learning | 60205 | 7.5 credits | 7.5 | |||
| SF2943 Time Series AnalysisIncluded in Theory, Statistics & Probability | 60213 | 7.5 credits | 7.5 |
Recommended courses
| Course code and name | Appl.code | Scope | P1 | P2 | P3 | P4 |
|---|---|---|---|---|---|---|
| DD2395 Computer Security | 6.0 credits | 6.0 | ||||
| ID2221 Data-Intensive Computing | 7.5 credits | 7.5 | ||||
| DD1388 Program System Construction Using C++ | 60196 | 7.5 credits | 4.0 | 3.5 | ||
| DD2352 Algorithms and Complexity | 60203 | 7.5 credits | 3.0 | 4.5 | ||
| DH2642 Interaction Programming and the Dynamic Web | 60195 | 7.5 credits | 4.5 | 3.0 | ||
| DD2448 Foundations of Cryptography | 60262 | 7.5 credits | 7.5 |