PROGRAM:

M.Eng. in Data Science & Artificial Intelligence

MODE:

Full-time, On-site

LEVEL:

Master of Engineering

LANGUAGE :

English

DURATION :

4 Semesters

LOCATION:

Munich, Siemens Neuperlach Campus

CREDITS :

120 ECTS

PRICE:

4.800 € / Semester

START DATE:

October 2026

SCHOLARSHIPS:

Up to 80% for high-performing students.

The Master’s program in Data Science and Artificial Intelligence (AI) at MUDT is designed for ambitious students seeking to drive innovation in AI-powered systems. This interdisciplinary program offers a robust combination of advanced theory and applied skills in machine learning, data engineering, ethical AI, and emerging fields such as large language models (LLMs), computer vision, and generative AI.

Students will engage in real-world projects and thesis work in close collaboration with academia or industry, preparing them for cutting-edge roles in tech, business, and research.

The Master of Engineering in Data Science & Artificial Intelligence is planned to launch in October 2026 and is currently undergoing the accreditation process.

Applications will open in Jan 2026, and you are welcome to apply starting from that date.

Specialisations

As you advance through the program, you can tailor your studies to your interests and career goals. With eight elective modules and the option to choose courses across multiple engineering programs, you can build a personalised focus area. These specialisations help you deepen your expertise—whether in machine learning, cloud systems, robotics, IoT, industrial AI, or business analytics—and prepare you for the roles most in demand in today’s technology landscape.

Why Study This Program at MUDT?

Industry-Driven Curriculum: Built in collaboration with AI experts and industry leaders.

Specialization in Emerging Tech: Deep dive into LLMs, responsible AI, causal inference, and more

Location Advantage: Study in Munich, a leading European tech hub.

Hands-On Projects: Collaborate with companies on real data and AI challenges.

Entrepreneurship Focus: Develop business-ready AI products with startup and innovation modules.

Study Program: M.Eng. in Data Science & Artificial Intelligence

This Master’s program is structured around advanced core modules, specialised electives, personal development courses, an industry internship, and a research-based Master thesis. The curriculum combines deep technical learning with practical projects, giving students the skills to build and deploy modern AI systems in real engineering environments.

Summary of Credits

Semester 1 :
Foundations & Core AI Systems

ECTS

Core Modules:

1.Foundations of Deep Learning & Generative Models – 5 ECTS

2.Large Language Models: Architecture & Applications – 5 ECTS

3.Architectures of Intelligent Agents – 5 ECTS

4.MLOps & AgentOps: Deploying AI Systems – 5 ECTS

5.Trustworthy AI: Alignment, Ethics & Governance – 5 ECTS

Personal Development:
6. Personal Development: Intercultural Communication – 5 ECTS
7. Foreign Language (German or other) – 5 ECTS

Semester 2 :
Advanced Architectures & Multi-Agent Systems

30 ECTS

Core Modules:

1.Advanced Reasoning: RAG & Knowledge Graphs – 5 ECTS

2.Multi-Agent & Collaborative AI Systems – 5 ECTS

Elective (choose 1): (6 ECTS)
3. Elective I – 6 ECTS

4. Elective II – 6 ECTS

Personal Development:
5. Personal Development: Teaming Up – 4 ECTS (from PD module group)

6. Career Planning

Semester 3 :
Practical Experience & Advanced Specialization

ECTS

Industry Experience:

1.Mandatory Internship

Semester 4 :
Research & Thesis

30 ECTS

Master Thesis & Research:

1.Master Thesis

2. Master Thesis Seminar / Defense Preparation

Elective (choose 1):

3. Elective III – 6 ECTS

4. Elective IV – 6 ECTS

Personal Development:
5. Career Planning II (Final Module) – 4 ECTS

Elective Courses – Personalize Your Study Journey

Students select four electives across Semesters 2, 3, and 4

AI in Simulation & Digital Twins (6 ECTS)

Develops skills for simulation environments, digital twins, robotics training, sim-to-real transfer, and domain randomization using tools like NVIDIA Isaac Sim and Gazebo.
Autonomous Software Development (6 ECTS)

Focuses on AI-assisted software engineering, code-specialized LLMs, automated testing, and debugging using next-generation AI development tools.

Advanced Cloud Architectures for AI (6 ECTS)

Teaches scalable cloud-native AI deployment including Kubernetes, distributed systems, and high-performance compute environments.
Generative AI for Creativity & Innovation (6 ECTS)

Explores advanced generative models for automation, media creation, innovation pipelines, and enterprise workflows.

Robotics & Embodied AI (6 ECTS)

Applies AI models to robotic systems, control algorithms, and embodied intelligence.

Who Should Apply?

This program is ideal for students who:

have a Bachelor’s degree (Especially Engineering, AI, Data Science, Business, etc.)
want to build and deploy advanced AI systems (LLMs, agents, MLOps, cloud AI),
enjoy solving complex problems with cutting-edge technologies,
aim for careers like AI Engineer, ML Engineer, AI Architect, or Autonomous Systems Developer,
are curious about ethical, secure, and responsible AI,
and prefer hands-on, project-based learning connected to industry.

Qualification Goals

1

Advanced Scientific & Technical Expertise

Graduates gain deep knowledge of modern AI systems, including deep learning, LLMs, intelligent agents, multi-agent architectures, RAG systems, cloud-native AI, and trustworthy AI. They can design, implement, and evaluate complex AI solutions at a professional engineering level.

2

Application of AI in New & Complex Contexts:

Graduates can apply advanced AI methods in unfamiliar, multidisciplinary environments such as industry, business, robotics, simulation, and digital twins. They can integrate diverse technologies and manage complexity.

3

Responsible & Ethical AI Competence:

Graduates understand the societal, ethical, and regulatory implications of AI. They can ensure fairness, transparency, privacy, security, and alignment when developing AI systems and comply with frameworks like the EU AI Act.

4

Communication & Leadership Skills:

Graduates can clearly communicate technical results to expert and non-expert audiences, lead technical projects, work in diverse teams, and take responsibility in collaborative and interdisciplinary settings.

5

Self-Directed Professional Growth:

Graduates are prepared for independent learning, research, and innovation. They can manage their own development, pursue advanced specialization, or continue toward a PhD or research career.

Career Opportunities, Salaries & Job Growth in Germany

Graduates of the M.Eng. in Data Science & AI are highly sought after across Germany’s technology, engineering, and industrial sectors. Typical career paths include AI Engineer, Machine Learning Engineer, AI Architect, Cloud & MLOps Engineer, Autonomous Systems Developer, and Data Scientist.

Germany offers one of Europe’s strongest job markets for AI talent, with starting salaries typically between €55,000–€75,000, rising to €90,000–€120,000+ with experience and specialization. Demand continues to grow due to rapid digital transformation, Industry 4.0, automation, and the adoption of AI in manufacturing, healthcare, finance, logistics, and consulting.

The demand for AI talent in Germany is expected to grow by over 25% annually, driven by digital transformation, Industry 4.0, and EU-backed AI investments.

{ By joining this Master of Engineering in Data Science & AI, you gain the expertise, industry experience, and technological insight needed to lead innovative AI projects, shape intelligent systems, and build a successful career in one of Germany’s fastest-growing and most impactful fields. }

Faculty Expertise:

Meet our esteemed faculty members who bring a wealth of experience and expertise in cyber security, ethical hacking, and threat intelligence. Learn from industry practitioners dedicated to shaping the next generation of cyber security professionals.

BIO

Prof. Dr. Pawel Gburzynski

How to apply

Submit Your Application:

Create an account, select your study program, and upload the required documents. We’ll confirm once everything is submitted.

Pass the Interview:

If your documents are approved, you'll be invited to an online interview. Succeed, and you'll receive a conditional acceptance.

Sign and Pay:

Return the signed study contract and complete the enrollment fee and deposit to secure your spot