Data Science

The MSc Data Science offers a comprehensive education in the concepts and methods of data science, incorporating knowledge and methodology from Computer Science and Mathematics. Special emphasis is placed on the sound training of fundamental (mathematical) concepts as to be able to competently assess the properties and limitations of the methods. As the programme includes compulsory courses in mathematics and computer science, we expect candidates to have a strong background in both areas. The main topics are:  Machine Learning (ML), AI, and Deep Learning  Statistics, Matrix Algorithms, and mathematical foundations of ML  Data Structures, Algorithms and Optimisations for Big Data  Data Engineering with Big Data Infrastructures and Data Wrangling  The programme offers a wide range of application areas in collaboration with adjacent departments: Medicine, Economics, Engineering, Geography, Material Science, Physics and others. It provides close connections to industry and research. The field of data science as a modern interdisciplinary science underpins the process of digitalisation and the effective utilisation of data in many application areas. The programme consists of the following course categories (called module groups) Core Data Science Methods (32 credits) Algorithms and Data Engineering Machine Learning Mathematical Foundations Advanced Data Science Methods / Elective Courses (at least 36 credits) Broad range of elective modules in mathematics and/or computer science, e.g. Quantum Algorithms, Statistics, Optimisation, Modelling, Deep Learning, etc. Scientific Project Work Data Science Project (10 credits) Seminar: Mathematics and Computer Science (4 credits each) Social Aspects of Data Science / Ethics (4 credits) Master's Thesis (30 credits) Tips on how to organise your studies can be found in our FAQs: https://www.uni-augsburg.de/en/fakultaet/fai/informatik/studienangebot/msc-dsc/#faq_contacts.