The following courses are part of study year two.
The course application codes and study periods are valid for the academic year 2018/2019. For other academic years, different application codes and study periods may apply
General Courses
A.1.2. Common Elective Courses
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.
A student must take at least 4 courses from the grouping listed in A.2 and at least 2 courses from the group of courses in A.3 and A.4.
A.2 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 credits
VISUALIZATION:
DD2257 Visualization, 7,5 hp.
ROBOTICS:
DD2438 Artificial Intelligence and Multi Agent Systems, 15 hp,
DD2425 Robotics and Autonomous Systems, 9 hp.
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.
MACHINE LEARNING:
EQ2341 Pattern Recognition and Machine Learning, 7,5 hp,
DD2432 Artificial Neural Networks and Other Learning Systems, 6 hp.
ID2223 Scalable Machine Learning and Deep Learning 7.5
ID2222 Data Mining 7.5
A.3 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.
A.4 Conditionally Elective Courses - Computer Science
PARALLEL COMPUTING:
SF2568 Parallel Computations for Large- Scale Problems, 6 hp
ID2221 Data-Intensive Computing, 7.5 credits
THEORY:
DD2352 Algorithms and Complexity, 7,5 hp.
Software Engineering:
DD1388 Program System Construction Using C++, 7,5 hp. (only in Swedish)
DH2642 Interaction Programming and the Dynamic Web7.5 hp
ID2213 Logic Programming, 7.5 hp
Databases:
DD1368 Database Technology, 6 hp
Security:
DD2395 Computer security, 6 hp
DD2448 Foundations of Cryptography, 7,5 hp
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 |