Artificial Intelligence & Data Science
Master´s degree program at UAS Technikum Wien
The application deadline for applicants within the EU is May 31, 2026, and for applicants outside the EU, March 31, 2026.
Shape the Future with AI
The AI program for professionals who want to combine career and academic growth while gaining deep, hands-on expertise in AI technologies. Our updated AI Master’s program will start in fall 2026 (subject to accreditation by AQ Austria). Applications are already being accepted.
Bridging Theory and Application
Intelligent systems are already deeply embedded in our lives: generative AI creates text, images, and code; chatbots and virtual assistants interact naturally with users; autonomous systems navigate cars and drones; and smart devices coordinate connected homes. In science and medicine, AI models predict protein structures, accelerate drug discovery, and support diagnostics through large-scale image and data analysis.
UAS Technikum Wien offers an updated AI Master’s program for professionals with a technical or analytical background who want to deepen their expertise in AI and data-driven technologies. Students learn to connect data and decision-making, designing AI solutions that create real value across business, technology, and society. The curriculum provides an in-depth grounding in AI algorithms and computational methods, enabling the students to build intelligent systems or apply cutting-edge frameworks. Through hands-on projects, students tackle real-world challenges in automation, analytics, and intelligent decision-making while developing leadership and innovation skills for global AI-driven environments.
Evening classes, small groups, and close ties with industry partners ensure that your studies remain relevant, applicable, and future-oriented.
Facts
- Start of semester: September
- Duration: 120 ECTS credits, 4 semesters
- Degree: Master of Science (MSc)
- Language: English (new from 2026/27)
- Mode: Part-time (evening form)
- Costs per semester: € 363.36 tuition fee, € 25.20 ÖH fee; € 3,000 Tuition fee for students from third countries: exceptions and information
- Recommended semester abroad (optional): 3, 4
Curriculum Overview
1st Semester – Fundamentals and Methodology
In the first semester, students acquire the technical and methodological foundations for the advanced courses in later semesters. They learn core methods of machine learning, statistical modeling, and data preprocessing. Complementary courses in software engineering provide the skills needed to develop reproducible and maintainable ML systems.
2nd Semester – Specialization and Two Electives
In the second semester, students deepen their knowledge and apply it in practice-oriented projects. Alongside advanced machine learning methods (Deep Learning Architectures, Ensemble Learning, etc.) and the Research Paper Seminar, students choose one of three options for each of two elective modules.
Elective 1:
a) Natural Language Processing AI: language models, text understanding, semantic analysis
b) Evolutionary and Logic-Based AI: symbolic and evolutionary AI methods
c) Data Warehouse & Business Intelligence: analytical data architectures, decision support
Elective 2:
a) Computer Vision AI: image processing, visual recognition
b) Big Data Analytics: distributed data processing, scalable analytics
c) Predictive Maintenance: data-driven reliability and forecasting models
In parallel, students work on real-world AI & Data applications in PBL projects and learn to critically interpret and practically implement research findings.
3rd Semester – Integration and Two Additional Electives
The third semester focuses on the professional application and integration of advanced AI & Data systems. In addition to core modules on MLOps, AI & Data Law, AI & Data Ethics, and Special Chapters in AI & Data Science, students select two further specializations.
Elective 3:
a) Machine Learning Engineering: scalable, production-ready ML systems
b) Autonomous AI Systems & RFL: decision-making and reinforcement learning
c) Data Science with R: data analytics and statistical modeling in R
Elective 4:
a) Robotics AI: autonomous systems and robotics
b) Explainable and Trustworthy AI / AI Security: explainable, secure, and fair AI
c) AI-driven Marketing: data-driven strategies and AI applications in marketing
4th Semester – Thesis
In the final semester, the focus is on the master’s thesis. Students design and carry out an independent research or development project, document their results scientifically, and defend their thesis.
A detailed curriculum can be found here:
Examples of past Student AI Projects
Career Prospects
Through elective courses this AI Master program gives you the flexibility to focus your studies in the direction that suits you best — as an AI Engineer, creating intelligent systems, or as a Data Scientist, transforming data into meaningful decisions.
Potential career paths include but are not limited to:
- AI Engineer / Machine Learning Expert
- Data Scientist / Data Engineer
- AI Project Manager / Product Owner
- Innovation & Business Development Expert
- Researcher or Consultant in AI-driven Transformation
Requirements
You must meet subject-matter requirements to be admitted to the Artificial Intelligence & Data Science master’s degree program. Prerequisites include a bachelor’s degree from a UAS in a relevant subject matter or an equivalent degree program with at least 180 ECTS credits – for example:
- computer science, software: software engineering, computer science, business informatics, mobile computing, computer security, information and communication systems, IT security, geoinformation
If basic equivalence has been established except for a few missing prerequisites, the program director can require students to take exams to establish full equivalence. These exams are taken during the master’s program.
For this, a minimum of approximately 60 ECTS should be brought from the following core subject areas:
- Computer science (e.g. programming, databases, operating systems, computer networks)
- Mathematics
- In-depth technical subjects
In any case, profound programming knowledge is a mandatory prerequisite to fulfill the admission requirements.
Contact
Program Director Master Artificial Intelligence & Data Science
Administrative Assistant
Master Data Science / Master Artificial Intelligence & Data Science
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Application
The next step to study Master Artificial Intelligence & Data Science is to apply via our online application system:
- The entire application process is handled via a dedicated application website.
- Your data is stored securely and is being treated with strict confidentiality.
- A registration system makes it possible to start an application and complete it at a later point in time.
- Once you have entered your user data and uploaded documents, you can also use them for subsequent applications.
