MSc Data Science (Research Master's)

CONCEPT In this innovative project-based Master's programme, you will become a data scientist within the area of applied research. You will apply for a research project before the start of the programme and work on it under the close supervision of proven experts throughout the entire Master's programme. This puts you in a position to apply the basic knowledge you have learned directly in practice and thus internalise it in the long term. The Research Master's in Data Science trains engineers for a career in applied science as well as a professional future in the industry. In this unique programme, they become scientists during their Master's degree and publish their work at international conferences in Hamburg, Italy and the USA. After graduation, 50% of graduates begin a doctoral thesis and 50% work as data scientists in the industry. MOTIVATION Data science is one of the most important disciplines of the digital age. Almost all objects and processes in the physical world are gradually mapped in the digital world. More and more digital twins are being created to store and make unimaginable amounts of data and new groundbreaking developments available in the field of artificial intelligence. This data changes the way we work, learn and live. As a data scientist, you will not just passively experience this digital revolution, but actively shape it. STUDY OBJECTIVES The Research Master's programme trains you to become an applied scientific researcher in the field of data science. The following study objectives will be achieved: Mastering data mining methods and algorithms for processing, analysing and exploiting large amounts of data Ability to apply machine learning algorithms to develop decision support systems based on large amounts of data Development of generative models for the generation of images, videos and text In-depth expertise in the development of autonomous software agents based on artificial intelligence Developing, configuring and using big data architectures for batch and stream processing Mastery of multi-paradigmatic programming with Python and its relevant ML libraries Students will gain the ability to perform independent, applied scientific work in interdisciplinary project teams. This includes writing research abstracts, preparing scientific publications, discussing and defending one's own results in a plenary session. Mastering agile project management skills to lead innovative project teams The ability to reflect on one's own work, especially in light of the limits of scientific knowledge and ethical considerations First semester: Project Phase I (12 ECTS) Introduction to Applied Research (6 ECTS) Compulsory elective subject Data Science Introduction to Data Science (6 ECTS) Scientific interchange (1 ECTS) Project-specific elective module (5 ECTS) Second semester: Project Phase II (7 ECTS) Agile Research Project Management (6 ECTS) Compulsory elective subject Data Science (6 ECTS) Compulsory elective subject Data Science (6 ECTS) Project-specific elective module (5 ECTS) Third semester: Project Phase III (12 ECTS) Social implication of Data Science (6 ECTS) Compulsory elective subject Data Science (6 ECTS) Scientific interchange (1 ECTS) Project-specific elective module (5 ECTS) Fourth semester: Master's thesis (24 ECTS) Colloquium (6 ECTS) Compulsory elective subject Data Science: Introduction to Data Science Big Data Architectures Data Mining & Machine Learning Artificial Intelligence Advanced Machine Learning Artificial Intelligence for Robotics PDF Download