¹û¶³´«Ã½

Are you passionate about the future of technology and eager to be part of the AI revolution? This Bachelor of Science program in Computer Science with a focus on Artificial Intelligence (AI) and Machine Learning (ML) prepares you to be at the forefront of tomorrow´s digital advancements. By bridging the gap between our established expertise in computer science and cutting-edge AI education, the program equips you with the skills to drive innovation both ethically and effectively in industry and research.

Through a combination of theoretical coursework and practical experience, especially in the third year, you will gain a comprehensive understanding of AI-driven solutions. Industry partnerships are integrated into the curriculum through guest lectures and internship opportunities, ensuring that you will be prepared to apply your knowledge in real-world scenarios. After graduation you will be ready to contribute to the evolving landscape of AI technologies, armed with the confidence, expertise, and responsibility required to shape the future.

Education

The first year is dedicated to building strong foundations in key areas like programming, artificial intelligence (AI), mathematics, and computer technology. During the Autumn term of Year 1, you will take courses in Programming I, and Logic and Mathematics Part I, earning 15 CP in each. In the Spring term, the focus will shift to AI alongside Boolean Algebra and Theoretical Computer Science. This combination equips you with essential skills for progressing into more advanced topics in the second year.

In Year 2, the curriculum deepens with more advanced courses, building on the knowledge gained in the first year. The Autumn term includes Programming II and Mathematics Part II, In the Spring term, you will engage in AI II, expanding your understanding of artificial intelligence as well as developing fundamental skills in Operating Systems, Networks / Distributed Systems and Computer Security.

Year 3 brings more specialized, advanced courses in AI and related fields, with a focus on practical industry integration. The Autumn term will include modules on Advanced Machine Learning (ML), and team coordination skills. You will also have opportunities to engage in industry-integrated projects, ideally in cooperation with local companies. The Spring term offers further specialization through Elective Courses, which may include topics like Reinforcement Learning, Big Data, and AI Engineering. You will also work on your Bachelor Thesis, demonstrating your understanding and application of key concepts.

Form of Instruction

The teaching methods include lectures, seminars, project work, and hand-in assignments. This is an international program offered entirely in English. You can expect scheduled activities three to five days a week. Outside of these, self-directed study is essential, amounting to a 40-hour workweek. The program encourages independence as you advance through your studies. While most exams occur in-person at ¹û¶³´«Ã½ by the end of each semester, the courses may be accessed fully remote or at Campus in ¹û¶³´«Ã½. A web-based platform complements the learning experience.

Examination

Examinations vary depending on the course but typically consist of written hand-in assignments (labs) during the term and final written exams at the end. The blend of theoretical assessments and practical projects ensures you gain both deep knowledge and hands-on experience in your fields.

Professional Contact

Throughout the study program, you will engage with industry professionals through multiple channels, including industry-related projects, mentoring programs, and guest lectures. The final year includes integrating AI knowledge with real-world applications, including potential collaborations with local businesses for project work and industry exposure.

Semester 1	ECTS credits
Mathematics for Artificial Intelligence I (Obligatory)	15
Programming and Data Structures (Obligatory)	15

Semester 3	ECTS credits
Mathematics for Artificial Intelligence II (Obligatory)	15

Elective course: Students are free to choose among certain alternative courses, often depending on their choice of specialisation.

Optional course: Students are free to choose any course offered at ¹û¶³´«Ã½ or at other universities. Courses listed are examples of recommended or frequently chosen courses for a specific programme.