SRH University is a state-recognized private university in Germany with multiple campuses across the country and a strong focus on applied, industry-aligned study programmes taught in English. The university promotes practical learning supported by its unique CORE learning approach — combining subject knowledge, practical skills and professional competencies to prepare students for careers in global industries.

 

Why Study Applied Data Science and Artificial Intelligence at SRH?

• English-taught Master's — no German required for instruction.
• Industry-focused curriculum blending data science, machine learning, ethical AI, cloud computing and domain applications.
• Multiple specialisation tracks across campuses — such as Business Analytics, Logistics, Creative AI and Life Sciences.
• Hands-on projects, workshops and internships for practical experience.
• Strong career outcomes — prepares for roles in tech, consulting, healthcare, finance, research and more.

 

Subjects / Programme Structure

The Master’s curriculum is practical, future-focused and industry-aligned. Core modules generally include:

Foundational & Core Topics

• Advanced Mathematics & Statistics for Data Science

• Python for Data Science

• Machine Learning & Deep Learning

• Data Engineering & Big Data Processing

• Data Visualization & Storytelling

• Cloud Computing (AWS, Azure, etc.)

• Ethical & Responsible AI

• Research Methods & Innovation

• Industry Case Studies

• Master’s Thesis Project

6-Month Internship / Semester Abroad

• Option to gain real hands-on experience or global exposure.

Specialisation Tracks

You can tailor your expertise by choosing a track such as:

1. Business Analytics — focus on data-driven business strategy and consumer analytics.
2. Supply Chain & Logistics Analytics — predictive models and optimisation for operations.
3. General Track — broad advanced skills in AI, machine learning and engineering.
4. Creative AI & Media Analytics — generative AI, content analysis and creative systems.
5. AI-Driven Bioinformatics & Life Sciences — advanced machine learning for biomedical data.

 

Highlights of the Programme

• Industry Focus: Objective-oriented curriculum designed with real-world applicability.
• Practical Tools & Certifications: Includes optional professional certificates (e.g., SAS Visual Business Analyst, NVIDIA Deep Learning).
• Agile & Project Training: Basic agile methods (e.g., Scrum) included for data projects.
• CORE Learning Model: Combines soft skills (communication, leadership) with technical expertise.

 

Career Outcomes & Roles After Graduation

Graduates are prepared for a wide array of high-demand data and AI careers, including:

Data Science & Analytics

• Data Scientist

• Business Intelligence Analyst

• Quantitative / Data Analyst

• Research Data Scientist

• Forecasting Specialist

Machine Learning & AI

• Machine Learning Engineer

• AI Developer / AI Engineer

• Deep Learning Specialist

• Computer Vision Engineer

• NLP Engineer

• MLOps Engineer

Data Engineering & Cloud

• Data Engineer

• Cloud AI Engineer

• Big Data Engineer

• ETL / Pipeline Developer

• Data Platform Architect

Employer Examples (Past Graduates)

Graduates have found roles at companies such as Airbus, Bosch, BMW, Deloitte, SAP, PWC, Adidas, Accenture and many others across sectors. They may also pursue research roles or doctoral studies.

 

Visa & Immigration (International Students)

If you’re a non-EU/EEA student (e.g., from India):

• German student visa is required to study in Germany.
• You must provide your letter of admission, financial proof (bank statements/blocked account showing ~€934/month), health insurance and accommodation plan at visa application.
• After arrival in Germany, apply for a residence permit for study.
• Students are usually allowed to work part-time (e.g., ~120 full days or 240 half days per year) under the student visa rules.

 

Latest Updates & Key Notes

• A special campus location addition: Munich is now listed as a study site as it continues accreditation expansion.
• The curriculum emphasises ethical and responsible AI, a growing requirement in global tech sectors.
• Many students have reported the admission interview component in practice — preparation may include technical and motivational questions.