Intelligent Adaptive Systems

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 in which intelligent behaviour is considered the standard for computer systems.
The Intelligent Adaptive Systems (IAS) curriculum is focused on 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 where teamwork is promoted and extended in extracurricular discussions and activities. Thanks to the programme's proximity to current research projects, students can avail of a smooth transition into collaborative research environments and continuing education and study.

Educational organisation

The Master's programme comprises 120 credit points, distributed between compulsory core modules (48 CP), selectable focus (18 CP) and extending modules (12 CP), and project work (42 CP).

Semester one:
Software Architecture (6 CP)
Bio-Inspired Artificial Intelligence (6 CP)
Intelligent Robotics (6 CP)
+ 12 CP Focus Choice

Semester two:
Neural Networks (6 CP)
Databases and Information Systems (9 CP)
Algorithmic Learning (9 CP)
+ 6 CP Focus Choice

Semester three:
Research Methods (6 CP)
Project with integrated Seminar (12 CP)
+ 12 CP Extension Choice

Semester four:
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. All core modules consist of a combination of lecture and seminar/tutorial to foster student participation and constant application of learned concepts.

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 which 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. This list contains single modules that supplement core lectures as well as suggested sets of lectures that together form a coherent focus area. It will be reviewed on a regular basis to reflect current research and to include newly emerged and complementary teaching areas.
Currently, the choices for focus options include:

• Language Processing
• Image Processing
• Robot Technology
• Mobile Systems and Networks
• Knowledge Processing

Extension Choice:
12 credit points can be selected from a range of modules taught at the Department of Informatics or other departments as well as independent study projects. In comparison to the focus options, these modules can be used to gain knowledge in fields that go beyond the scope of this programme, but are linked to its contents, e.g. psychology or biology. The modules are again chosen in consultation with an adviser to guarantee a sensible choice in alignment with the student's background and aims.

Project and Thesis
Having participated in lectures and seminars where the focus is usually on individual work, students take part in a group project before undertaking a research project that finally leads to the Master's thesis. The group project focuses on teamwork and the scientific exchange and defence of ideas to prepare students for a collaborative scientific environment. Students are encouraged to choose projects in preparation of their Master's thesis and to actively take part in research projects of a chosen area. Two to three students are expected to work as an independent group with a supervisor from the corresponding area. A seminar, where all groups meet, gives students the opportunity to present their work in an environment comparable to a scientific conference.
Finally, in the last semester, students work full-time on an independent research project that ends with submission of the final Master's thesis.

Part-time study is possible. Reference semesters are doubled, and required credit points per semester amount to half of those required in full-time study. Prerequisites for lectures must be met, with courses available only in winter or in summer to be taken at the next opportunity.

Study abroad unit(s)

No study abroad periods are planned within the curriculum.

Forms of assessment

Assessment of lectures is generally via 30-minute oral exams. Few written exams. Seminars, tutorials, and the project are assessed through in-course work (e.g. software development, reports, and oral presentations).

Course objectives

The IAS Master's programme is a research-oriented programme which aims to provide students with a comprehensive overview in intelligent adaptive systems. Students who successfully complete the course will have in-depth knowledge on the state of the art in neural networks and learning algorithms for intelligent systems and will know how to integrate these into robots, databases, and information processing systems. Through focus and extension choice slots, students can further select focus areas to deepen their knowledge in IAS core areas or to extend their study to other areas.

Language requirements

All applicants must provide proof of their English language proficiency by (or comparable to):

• CEFR/TELC level B2
• IELTS 6.5
• TOEFL (iBT 90, PBT 575, CBT 230)
• Cambridge CAE or CPE

Academic requirements

A Bachelor's degree from Universität Hamburg or another university in computer science or a related field in which 60 CP were acquired in the field of computer science, comparable to the curriculum of the BSc "Informatik" (Computer Science) at Universität Hamburg. Comparability of the degree will be established by the admission commission.

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Want to improve your English level for admission?

Prepare for the program requirements with English Online by the British Council.

• ✔️ Flexible study schedule
• ✔️ Experienced teachers
• ✔️ Certificate upon completion

📘 Recommended for students with an IELTS level of 6.0 or below.

Enroll in the course

Enrolment fees

There is a semester fee of 310 EUR per semester. This fee includes a semester ticket covering public transport in the Hamburg metropolitan area.

Costs of living

We recommend that single students budget at least 800 EUR per month to meet personal expenses (accommodation, living, health insurance, books).

Job opportunities

Students who enrol in a full-time programme will generally have only limited time for part-time jobs.
As a rule, students who hold an international student visa may work for up to 120 full days or 240 half days per year. Further information on work regulations for international students at Universität Hamburg can be found here: http://www.uni-hamburg.de/piasta/beratung_e.html

Funding opportunities within the university

International full-time students may apply for merit scholarships or exam grants of Universität Hamburg. For more information, please use the provided link. We also recommend contacting our colleagues in the Department of International Affairs for further guidance.
http://www.uni-hamburg.de/internationales/studieren-an-der-uhh/finanzierung-des-studiums_e.html

Arrival support

Students and researchers can find information on how to get started in Hamburg on the website of the PIASTA programme at the Universität Hamburg Department of International Affairs (http://www.uni-hamburg.de/piasta_e.html) and on the website of the Hamburg Welcome Center (http://english.welcome.hamburg.de).
During the International Welcome Week organised by PIASTA, you will be able to get in touch with all the important institutions and contacts which are particularly useful for international students: http://www.uni-hamburg.de/piasta/veranstaltungen/international-welcome-week_e.html

Services and support for international students

The Universität Hamburg CampusCenter is the first port of call for all current and prospective students and offers information, services, and counselling. The PIASTA programme at the Universität Hamburg Department of International Affairs offers support and advice for German and international students, as well as cultural events and workshops.
For more information, refer to: http://www.uni-hamburg.de/piasta and https://www.uni-hamburg.de/en/campuscenter.html
The welcome service of the Universität Hamburg Department of International Affairs is the first contact address for international visiting researchers and others: http://www.uni-hamburg.de/internationales/wissenschaft/service-international_e.html

Accommodation

Accommodation is available through the "Studierendenwerk" (students' services) or on the private market. The "Studierendenwerk" provides rooms in halls of residence, most of which are single rooms with shared kitchens and showers/WCs. We strongly advise students and researchers to arrange accommodation prior to arriving in Hamburg, as demand for affordable accommodation is sometimes larger than supply.
For more information on how to find accommodation and how to plan your first steps in Hamburg, please refer to: https://www.uni-hamburg.de/piasta/beratung/doc/willkommen.pdf