Study year 1

Master's Programme, Machine Learning, 120 credits (TMAIM), Programme syllabus for studies starting in autumn 2018

The following courses are part of study year one.

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

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.

Mandatory Appl.code Scope Study period
 1   2   3   4 
DD2380 Artificial Intelligence 6.0 hp 6.0
DD2421 Machine Learning 7.5 hp 7.5
DA2205 Introduction to the Philosophy of Science and Research Methodology 7.5 hp 3.0 4.5
DD2301 Program Integrating Course in Machine Learning 3.0 hp 0.5 0.5 0.5 0.5
DD2434 Machine Learning, Advanced Course 7.5 hp 7.5

Conditionally elective Appl.code Scope Study period
 1   2   3   4 
DD2257 Visualization 7.5 hp 7.5
DD2410 Introduction to Robotics 7.5 hp 7.5
DD2429 Computational Photography 6.0 hp 6.0
DD2437 Artificial Neural Networks and Deep Architectures 7.5 hp 7.5
SF2940 Probability Theory 7.5 hp 7.5
DD2425 Robotics and Autonomous Systems 9.0 hp 3.5 5.5
DD2435 Mathematical Modelling of Biological Systems 9.0 hp 6.0 3.0
DD2418 Language Engineering 6.0 hp 6.0
DD2423 Image Analysis and Computer Vision 7.5 hp 7.5
DD2447 Statistical Methods in Applied Computer Science 6.0 hp 6.0
EL2320 Applied Estimation 7.5 hp 7.5
EL2805 Reinforcement Learning 7.5 hp 7.5
ID2222 Data Mining 7.5 hp 7.5
ID2223 Scalable Machine Learning and Deep Learning 7.5 hp 7.5
SF1811 Optimization 6.0 hp 6.0
DD2411 Research project in Robotics, Perception and Learning 15.0 hp 4.0 3.5
DD2420 Probabilistic Graphical Models 7.5 hp 7.5
DT2112 Speech Technology 7.5 hp 7.5
SF2930 Regression Analysis 7.5 hp 7.5
DD2402 Advanced Individual Course in Computational Biology 6.0 hp 3.0 3.0
DD2438 Artificial Intelligence and Multi Agent Systems 15.0 hp 7.0 8.0
DD2476 Search Engines and Information Retrieval Systems 9.0 hp 6.0 3.0
DD2401 Neuroscience 7.5 hp 7.5
DD2424 Deep Learning in Data Science 7.5 hp 7.5
DT2119 Speech and Speaker Recognition 7.5 hp 7.5
EQ2341 Pattern Recognition and Machine Learning 7.5 hp 7.5
SF2943 Time Series Analysis 7.5 hp 7.5
Recommended Appl.code Scope Study period
 1   2   3   4 
ID2213 Logic Programming 7.5 hp 7.5
ID2221 Data-Intensive Computing 7.5 hp 7.5
DD2395 Computer Security 6.0 hp 6.0
DD1388 Program System Construction Using C++ 7.5 hp 4.0 3.5
DD2352 Algorithms and Complexity 7.5 hp 4.5 3.0
DD2448 Foundations of Cryptography 7.5 hp 3.0 4.5
DH2642 Interaction Programming and the Dynamic Web 7.5 hp 4.5 3.0
SF2568 Parallel Computations for Large- Scale Problems 7.5 hp 3.0 4.5