AI & Robotics (MSc) University of Technology Nuremberg

Artificial intelligence is a rapidly growing field that is changing the way we live and work. As a result, there is a growing demand for professionals with experience in robotics and artificial intelligence in various industries.

The Master's degree programme in Artificial Intelligence and Robotics provides students with the opportunity to develop advanced skills and knowledge in these exciting fields. By combining theoretical and practical courses with our new learning design, students will gain an in-depth understanding of the concepts, algorithms, and applications of robotics and artificial intelligence. They also learn to design, implement and evaluate complex robotic systems and artificial intelligence algorithms.

Graduates of the programme are equipped to pursue careers in a variety of industries, including manufacturing, healthcare, transportation, and entertainment. They are also ready to pursue research and academic opportunities in robotics and artificial intelligence.

As a graduate, you will...

… be able to apply theory-grounded and science-based content and methods for the innovative, effective and sustainable design or development of technologies for AI and robotics systems.

… have gained scientifically-based experience (content, methods, assignments) to develop and apply skills in data collection, analysis, and evaluation for AI and robotics systems.

… have gained scientific experience to create novel solutions of AI / robotics technologies in response to current and future challenges of emerging technologies.

… be able to work effectively, also in diverse teams, and continuously develop your own expertise and learning.

… demonstrate an awareness of sustainability and democratic citizenship, and reflect and relate your own actions and research to social and ethical contexts.

Study programme concept

Our innovative teaching and learning approach, rooted in extensive research, emphasises active engagement and reflective practices. Rather than memorisation-based learning, our approach entails students undertaking learning-oriented assignments throughout the semester as well as receiving personalised feedback from faculty on their progress.

The curriculum of the Master's programme in Artificial Intelligence and Robotics is a modularised study programme. Students will learn about problem-solving, decision-making, and knowledge representation in AI as well as the design and implementation of algorithms for autonomous robot navigation. They will study neural networks, training algorithms, optimisation techniques, and applications in computer vision and natural language processing. Students will also learn about data analysis, statistical methods, data visualisation, and data mining techniques. Through practical assignments and projects, they will gain hands-on experience in designing and implementing algorithms and systems in these fields.

The unique highlight is the Learning in Transformation Project, an interdisciplinary scientific research project that focuses on practical learning experiences. The project aims to provide students with a scientific-based approach to solving real-world problems. See the full curriculum here.

Please note that the Master’s in AI & Robotics is a full-time programme. You should plan about 40 hours of work per week.

Find out more about our teaching and learning concept here.

Curriculum:

Requirements Artificial Intelligence & Robotics (MSc)

• Bachelor of Science
  (or equivalent) in Computer Science or related fields such as Electrical Engineering, Mechanical Engineering, Mathematics, or Physics
• Excellent knowledge of Computer Sciences:
  • Introduction to Computer Science, Programming, Algorithms and Data Structures as well as one of the following subjects: Theoretical Computer Science, Computer Architecture, Computer Networks, or Software Engineering (minimum of 24 ECTS credits or equivalent)
• Mathematical references in analysis and linear algebra 
  (at least 18 ECTS or equivalent)
• Necessary programming competencies in algorithms and data structures:
  • Basic data structures (arrays, lists, stacks, queues, sets, trees, and graphs)
  • Complexity analysis (best case, worst case, average case, Big-O notation, divide and conquer)
  • Sorting algorithms (bubble sort, insertion sort, quicksort, merge sort, and heap sort)
  • Searching algorithms (linear search, binary search, tree search, and graph search)
  • Hashing techniques (open hashing and closed hashing)
• Proficiency in English (details below)
• Successful participation in the aptitude assessment procedure

The semester fee is 72 EUR.

International students can work for up to 120 full days or 240 part days per year, as noted on their residence permits. During the semester, work is limited to 20 hours per week to prioritise studies.

Options include working at the university as a research or student assistant, supporting teaching, research, or administration. Students may also work for companies in roles related to their studies or take up mini-jobs, which pay up to 520 EUR per month and are exempt from social security contributions. Part-time jobs allow higher earnings but require paying taxes and social security.

Please visit https://www.utn.de/en/study/working-as-a-student/ for further information or reach out to our Early Career Centre (stars-career@utn.de) after your arrival in Nuremberg.

Our Early Career Centre is the central point of contact for all students, doctoral candidates and post docs in the various career phases. We offer support tailored to individual needs and career paths. Our services include advice on career orientation and job applications as well as application training and networking. If you have any questions, please contact our Early Career Centre: stars-career@utn.de.

Accommodation in big cities such as Nuremberg can be scarce, especially in the weeks leading up to a new semester. To improve your chances of finding a suitable and affordable place to stay, it is recommended to start your search early and consider nearby areas as well. The well-connected public transport system of the region ensures easy access to your place of study or work, even if you live outside the city centre.

Student dormitories offer affordable, furnished rooms exclusively for students, with rents ranging from 200 to 600 EUR per month, depending on the provider and facilities, though waiting lists can be long. Shared apartments ("WGs" in German) provide a social atmosphere with reduced rent through shared living spaces, with monthly costs typically between 250 EUR and 500 EUR. Renting your own apartment offers privacy and flexibility, with prices ranging widely based on size and location, from around 500 EUR to over 1,000 EUR per month. For short-term stays or an initial solution, subleases or temporary accommodations (such as Airbnb or furnished rentals) can be convenient, with sublease rents similar to shared apartment prices and temporary rentals often costing significantly more (700+ EUR per month).

Please visit https://www.utn.de/en/study/accomodation-search/ for further information or reach out to our Welcome Centre (welcome@utn.de).