About this programme
Artificial Intelligence, Machine Learning, Neural Networks, Natural Language Processing, Computer Vision, Robotics, Human-Robot Interaction, Research Methods -- If you would like to learn about those topics and would like to have a bit of freedom for your own research topics, you should apply to the Master of Science programme in Intelligent Adaptive Systems at the Department of Informatics, Universität Hamburg, Germany. Intelligent systems and robots are expected to become an integral part of our daily lives. In order to be accepted by and to interact efficiently and naturally with humans, they have to adapt to changing environments as well as to the users they interact with. Intelligent systems are not only expected to automatically acquire and manage knowledge through a variety of sensors, but also to learn and optimise their behaviour over time. This International Master's programme aims to provide students with the ability to create these intelligent adaptive systems and to prepare them for a future market and career in academia in which intelligent behaviour is considered the standard for computer systems. The Intelligent Adaptive Systems (IAS) curriculum is focused on the intelligent adaptive behaviour of artificial systems, ranging from robots to computer systems. The selected modules provide a comprehensive overview, including technical aspects and state-of-the-art algorithms and methods. Students are introduced to current research in the corresponding fields and have the opportunity to deepen the acquired knowledge by participating in international research projects. The Master's programme in Intelligent Adaptive Systems is a two-year, research-oriented programme, taught in English. Students, both national and international, can profit from an international environment by improving their grasp of the English language and engaging in cultural exchange. This exchange is fostered in seminars and work groups in which teamwork is promoted and extended in extracurricular discussions and activities. Thanks to the proximity of the programme to current research projects, students can avail of a smooth transition into collaborative research environments and continuing education and study. Detailed information can be found here: https://www.master-intelligent-adaptive-systems.com/ Even more information on how to apply: https://www2.informatik.uni-hamburg.de/Info/Studium/MSc/IAS/wiki/index.php/Main_Page If you cannot find the information you are looking for, you may contact us via ias-team.inf@uni-hamburg.de. The IAS programme comprises 120 ECTS credit points, distributed between compulsory core modules (39 CP), selectable focus (24 CP) and extending modules (15 CP) and project work (42 CP). Semester 1: Software Architecture (6 CP) Bio-Inspired Artificial Intelligence (6 CP) Intelligent Robotics (6 CP) Research Methods (6 CP) + 6 CP Focus Choice Semester 2: Neural Networks (6 CP) Machine Learning (9 CP) + 12 CP Focus Choice + 3 CP Extension Choice Semester 3: Project with Integrated Seminar (12 CP) + 6 Focus Choice + 12 CP Extension Choice Semester 4: Master's thesis (30 CP) Core Lectures: Core lectures are compulsory for all students. This set of lectures conveys an in-depth understanding of different types of intelligent adaptive systems and introduces students to the most current research in the different topics. Focus Choice: Focus choice slots provide students with the opportunity to strengthen their background in a chosen field or deepen their knowledge in a field that complements the core modules. Focus modules will be chosen in consultation with an assigned adviser and can be selected from a list that aligns well with the overall focus of the Master's programme. Choices for focus options (currently): Language Processing Image Processing Robot Technology Knowledge Processing Cognitive Vision User Interface Software and Technology Speech Signal Processing Extension Choice: 15 credit points can be selected from a range of
Course details verified 10 Sep 2026 — intakes, entry requirements and course facts · official source