Advanced Studies in Signal Processing and Machine Learning, At least 60 cr

The major in Signal Processing and Machine Learning is designed for active and diligent students who are interested in the latest and still-developing technologies in information technology. At present, such topics include, for example, image, language, and sound processing, computer vision, machine learning, and robotics.

The module consists of two mandatory courses (10 cr) and a set of free-choice studies (20 cr). In terms of free-choice studies, students can create their own course package from the offered options or alternatively choose from the listed thematic specializations below.

Please note the possible prerequisites (order of course completion) when planning your studies.

Thematic specializations consist of the following subject areas and courses:

Imaging

• COMP.SGN.230 Vector Space Methods for Signal and Image Processing
• COMP.SGN.300 Advanced Image Processing
• COMP.SGN.320 3D and Virtual Reality
• COMP.SGN.330 Computational Imaging and Digital Holography
• COMP.SGN.350 Imaging sensors and systems

Machine hearing and vision

• COMP.SGN.220 Advanced Audio Processing
• COMP.SGN.340 Speech Processing
• COMP.SGN.300 Advanced Image Processing
• DATA.ML.300 Computer Vision

Signal processing and data analysis

• COMP.SGN.230 Vector Space Methods for Signal and Image Processing
• COMP.SGN.240 Advanced Signal Processing Laboratory
• COMP.SGN.300 Advanced Image Processing
• DATA.ML.330 Media Analysis
• DATA.ML.390 Computational Diagnostics of Data
• DATA.ML.430 Complex Networks

The module provides students with strong theoretical knowledge and practical skills in all the subject areas of our courses. Students are also welcome to become members of research groups during their studies.

• The student knows how to adopt, adapt and improve signal processing and machine learning methods for real problems.

• The student is able to find state-of-the-art methods and adapt them to to solve practical problems.

• The student knows the tools (Matlab) and software libraries (Python) for machine learning and signal processing problems.

• The student knows how to apply machine learning and signal processing methods in audio, speech, language, vision and robotic applications.