Starting date: September/February
Language requirements: English language proficiency (TOEFL 547/IELTS 6.0/oral examination)
The aim of the program is to train professionals who can understand the properties of different types of data and the structure of complex data sets, unfold the relationships inherent in the data, apply the necessary transformations to raw data to prepare it for analysis, analyze data, draw conclusions from the data, and model real-world processes. They will also be able to develop and manage data-oriented applications, perform and coordinate R&D tasks and continue their studies in PhD programs.
Lecture, seminar: 40%
Main subjects typically include (this list is indicative and may change):
|1||Machine Learning Fundamentals, Statistical Foundations of Data Science, Optimization in Data Science, Data Visualization Methods, Data-oriented Programming, Cloud Computing, Information Security, Data Ethics|
|2||Modern Deep Learning Frameworks, Advanced Machine Learning, Advanced Reinforcement Learning, Big Data Technologies, Advanced Robotics, Self-driving Cars, AI Security, Financial Models, Genetics and Big Data|
Internship, practice: Students should complete a 6-week internship either at the university working on research projects or at a multinational or local company.
More information about the program can be found here.
Career prospects: Data Science, MSc graduates have a comprehensive knowledge of the principles and methods of data science, as well as the technical background required to efficiently handle large and complex data sets. With these skills, graduates have a wide range of opportunities in a variety of industries, including positions such as data scientist, data analyst, data engineer, business analyst, or machine learning software developer.
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