The following courses are part of study year two.
The course application codes and study periods are valid for the academic year 2019/2020. For other academic years, different application codes and study periods may apply
General Courses
During year 1 and year 2 students must take at least complete 25 credits from the grouping listed in 1.2.1 and at least 13,5 credits from the group of courses in 1.2.2.
1.2.1 Conditionally Elective Courses - Application Domains
COMPUTER VISION:
DD2423 Image Analysis and Computer Vision, 7,5 hp,
DD2424 Deep learning in Data Science, 7,5 hp,
DD2429 Computational photography, 6 hp.
LANGUAGE PROCESSING: SPEECH & TEXT
DT2112 Speech Technology, 7,5 hp,
DT2119 Speech and Speaker Recognition, 7,5 hp
DD2418 Language Engineering, 6.0 hp
VISUALIZATION:
DD2257 Visualization, 7,5 hp
ROBOTICS:
DD2410 Introduction to Robotics, 7,5 credits
DD2438 Artificial Intelligence and Multi Agent Systems, 15 hp
DD2425 Robotics and Autonomous Systems, 9 hp
DD2411 Research project in Robotics, Perception, and Learning, 15 credits
DATABASES/INFORMATION RETRIEVAL:
DD2476 Search Engines and Information Retrieval Systems, 9 hp
COMPUTATIONAL BIOLOGY:
DD2435 Mathematical Modelling of Biological Systems, 9 hp,
DD2401 Neuroscience, 7,5 hp,
DD2402 Advanced Individual Course in Computational Biology, 6 hp,
DD2404 Applied Bioinformatics, 7,5 hp.
1.2.2 Conditionally Elective Courses - Theory
MATHEMATICS:
EL2320 Applied Estimation, 7,5 hp
SF1811 Optimization, 6 hp
STATISTICS & PROBABILITY:
DD2447 Statistical Methods in Applied Computer Science, 6 hp,
SF2930 Regression Analysis, 7,5 hp,
SF2943 Time Series Analysis, 7,5 hp,
SF2940 Probability theory, 7,5 hp.
MACHINE LEARNING:
EQ2340 Pattern Recognition 7,5 hp
DD2437 Artificial Neural Networks and Deep Architectures, 7,5 hp
ID2222 Data Mining 7.5
ID2223 Scalable Machine Learning and Deep Learning 7.5
DD2420 Probabilistic Graphical Models, 7,5 credits
EL2805 Reinforcement Learning, 7,5 credits
Common Elective Courses
Elective courses are selected freely from all Second cycle courses and language courses given at KTH. First cycle courses at KTH may be taken upon permission from the Programme Director. Not more than 30 ECTS credits in total can be acquired from First cycle courses.
Mandatory courses
| Course code and name | Appl.code | Scope | P1 | P2 | P3 | P4 |
|---|---|---|---|---|---|---|
| DD2301 Program Integrating Course in Machine Learning | 3.0 credits | 0.5 | 0.5 | |||
| DA233X Degree Project in Computer Science and Engineering, specializing in Machine Learning, Second Cycle | 30.0 credits | 15.0 | 15.0 | |||
| SF288X Degree Project in Optimization and Systems Theory, Second Cycle | 30.0 credits | 15.0 | 15.0 | |||
| SF299X Degree Project in Mathematical Statistics, Second Cycle | 30.0 credits | 15.0 | 15.0 |
Conditionally elective courses
Recommended courses
| Course code and name | Appl.code | Scope | P1 | P2 | P3 | P4 |
|---|---|---|---|---|---|---|
| ID2213 Logic Programming | 7.5 credits | 7.5 | ||||
| ID2221 Data-Intensive Computing | 7.5 credits | 7.5 | ||||
| DD2395 Computer Security | 6.0 credits | 6.0 | ||||
| DD1388 Program System Construction Using C++ | 7.5 credits | 4.0 | 3.5 | |||
| DD2352 Algorithms and Complexity | 7.5 credits | 4.5 | 3.0 | |||
| DH2642 Interaction Programming and the Dynamic Web | 7.5 credits | 4.5 | 3.0 | |||
| SF2568 Parallel Computations for Large- Scale Problems | 7.5 credits | 3.0 | 4.5 | |||
| DD2448 Foundations of Cryptography | 7.5 credits | 7.5 |