General courses

Year 1

Conditionally elective courses

Code Name Credits Edu. level
DD2257 Visualization 7.5 hp Second cycle
DD2401 Neuroscience 7.5 hp Second cycle
DD2402 Advanced Individual Course in Computational Biology 6.0 hp Second cycle
DD2410 Introduction to Robotics 7.5 hp Second cycle
DD2411 Research project in Robotics, Perception and Learning 15.0 hp Second cycle
DD2418 Language Engineering 6.0 hp Second cycle
DD2420 Probabilistic Graphical Models 7.5 hp Second cycle
DD2423 Image Analysis and Computer Vision 7.5 hp Second cycle
DD2424 Deep Learning in Data Science 7.5 hp Second cycle
DD2425 Robotics and Autonomous Systems 9.0 hp Second cycle
DD2429 Computational Photography 6.0 hp Second cycle
DD2435 Mathematical Modelling of Biological Systems 9.0 hp Second cycle
DD2437 Artificial Neural Networks and Deep Architectures 7.5 hp Second cycle
DD2438 Artificial Intelligence and Multi Agent Systems 15.0 hp Second cycle
DD2447 Statistical Methods in Applied Computer Science 6.0 hp Second cycle
DD2476 Search Engines and Information Retrieval Systems 9.0 hp Second cycle
DT2112 Speech Technology 7.5 hp Second cycle
DT2119 Speech and Speaker Recognition 7.5 hp Second cycle
EL2320 Applied Estimation 7.5 hp Second cycle
EL2805 Reinforcement Learning 7.5 hp Second cycle
EQ2341 Pattern Recognition and Machine Learning 7.5 hp Second cycle
ID2222 Data Mining 7.5 hp Second cycle
ID2223 Scalable Machine Learning and Deep Learning 7.5 hp Second cycle
SF1811 Optimization 6.0 hp First cycle
SF2930 Regression Analysis 7.5 hp Second cycle
SF2940 Probability Theory 7.5 hp Second cycle
SF2943 Time Series Analysis 7.5 hp Second cycle

Supplementary information

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 credits
DD2425 Robotics and Autonomous Systems, 9 credits
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:
EQ2341 Pattern Recognition and Machine Learning, 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.

Year 2

Conditionally elective courses

Code Name Credits Edu. level
DD2257 Visualization 7.5 hp Second cycle
DD2401 Neuroscience 7.5 hp Second cycle
DD2402 Advanced Individual Course in Computational Biology 6.0 hp Second cycle
DD2410 Introduction to Robotics 7.5 hp Second cycle
DD2411 Research project in Robotics, Perception and Learning 15.0 hp Second cycle
DD2418 Language Engineering 6.0 hp Second cycle
DD2420 Probabilistic Graphical Models 7.5 hp Second cycle
DD2423 Image Analysis and Computer Vision 7.5 hp Second cycle
DD2424 Deep Learning in Data Science 7.5 hp Second cycle
DD2425 Robotics and Autonomous Systems 9.0 hp Second cycle
DD2429 Computational Photography 6.0 hp Second cycle
DD2435 Mathematical Modelling of Biological Systems 9.0 hp Second cycle
DD2437 Artificial Neural Networks and Deep Architectures 7.5 hp Second cycle
DD2438 Artificial Intelligence and Multi Agent Systems 15.0 hp Second cycle
DD2447 Statistical Methods in Applied Computer Science 6.0 hp Second cycle
DD2476 Search Engines and Information Retrieval Systems 9.0 hp Second cycle
DT2112 Speech Technology 7.5 hp Second cycle
DT2119 Speech and Speaker Recognition 7.5 hp Second cycle
EL2320 Applied Estimation 7.5 hp Second cycle
EL2805 Reinforcement Learning 7.5 hp Second cycle
ID2222 Data Mining 7.5 hp Second cycle
ID2223 Scalable Machine Learning and Deep Learning 7.5 hp Second cycle
SF1811 Optimization 6.0 hp First cycle
SF2930 Regression Analysis 7.5 hp Second cycle
SF2940 Probability Theory 7.5 hp Second cycle
SF2943 Time Series Analysis 7.5 hp Second cycle

Supplementary information

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.