This English-taught MSc in Computer Science delivers a broad technical foundation combined with practical, career-oriented training. Core modules cover software development, cloud solutions, and data analysis alongside project and risk management. Throughout the program you’ll also strengthen agile working methods, business understanding and general soft skills through applied projects and a mandatory internship, helping you build a professional portfolio and workplace readiness.
The Big Data & Artificial Intelligence specialization deepens your competence in machine learning and AI techniques and shows how to harness big data and business intelligence to support strategic business decisions. Coursework and project work emphasize translating data-driven insights into actionable outcomes for organizations.
You can study at the Heidelberg campus (this programme is also offered in Leipzig) and choose a pace that fits your goals by selecting either the three-semester or the four-semester option.
Program details (concise)
Curriculum overview
This four-semester MSc track combines core computer science foundations with a strong focus on big data and artificial intelligence. The program front-loads technical coursework in the first two semesters—covering data engineering, analytics methods, software development and mathematical foundations—then moves into applied and research-oriented work in the final year. The structure is designed to build from theory to practice: students gain the algorithms and tooling knowledge needed for AI and data-driven systems, then apply those skills in industry or research settings before completing an independent master’s thesis.
Highlights of the taught portion include modules on advanced data technologies, machine learning (or an alternative advanced programming option), cloud-based solutions and Big Data/Business Intelligence. Coursework also covers practical topics such as agile project and risk management, open source intelligence and real-world AI use cases, preparing students to design, deploy and evaluate scalable data pipelines and intelligent applications. The program balances technical depth (advanced mathematics, algorithms, software development) with professional skills (project management, cloud deployment, ethical and applied considerations).
In the third semester students undertake an internship to gain hands-on experience in a professional or research environment. The final semester is devoted to scientific work and a comprehensive master’s project culminating in a thesis and oral defence. This progression ensures graduates are ready for roles that require both implementation skills and the ability to carry out independent research or lead data-driven projects in industry.
Key modules (by semester)
Intended learning outcomes
Program requirements (concise)
This master's program expects applicants to hold a relevant undergraduate degree and to provide standard application documents that verify identity, language ability, and motivation. International applicants should be prepared to explain how their prior studies relate to computer science, big data, or AI, and to submit clear copies of each required document.
Below are the documents you must submit as part of your application. Each item helps the admissions team assess academic background, language readiness, and your reasons for choosing the program.
Winter Semester (International)
15 August 2026
Summer Semester (International)
1 February 2027
Winter Semester (EU/EEA)
1 October 2026
Summer Semester (EU/EEA)
1 April 2026
Graduates are prepared for technical and applied roles where AI and data-driven decision-making are central. Typical career paths include data scientist, machine learning engineer, business intelligence analyst, AI consultant, and cloud/data engineer. The internship option in the four-semester track helps build industry contacts and practical experience that support transitions into professional roles.
The programme also provides a foundation for further research or doctoral studies for students interested in academic careers, since the final semesters include scientific work and a supervised Master's thesis.
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