Computational Intelligence

The English-language master program Computational Intelligence is concerned with the basics, the structure and design of intelligent agents. Additionally, it includes core elements of classical theoretical computer science.

• Algorithmics
• Algorithms and Complexity
• Knowledge-based Systems
• Knowledge Representation and Artificial Intelligence
• Formal Methods in Computer Science
• Programming Languages and Verification
• Discrete Mathematics
• Logic and Computability
• Logic, Mathematics, and Theoretical Computer Science

Requirements

• A degree from one of the following accredited national or international degree-granting programs (Bachelor, Master or Diploma): architecture, civil engineering, mechanical engineering, media computer science, software & information engineering, technical computer science or any other subject related field (if the field is subject related or not is decided by the dean of studies).
• Special entrance qualification for university (just if you are not a member of an EU/EWR country). 
• CV including relevant work experience (max. 3 A4 pages)
• Statement of intent (max. 2 A4 pages)
• Proficiency in English language. (CAE - minimum score 45, FCE – minimum grade C, IELTS Academic– minimum score 6.5, TOEFL iBT – minimum score 87)
• Proof of academic aptitude through recognized exams  (preferred GRE)

The financing options for the Master's degree program in Computational Intelligence at the Vienna University of Technology are designed to support students throughout their studies and provide accessible funding opportunities. Students can consider various sources of financial support, including government grants, scholarships, studentships, and university-specific funding schemes. Austrian residents and international students alike are encouraged to explore scholarships offered by the Austrian government, such as the Österreichischer Austauschdienst (OeAD) scholarships, which provide financial assistance to international students studying at Austrian institutions. Additionally, the university itself offers a range of scholarships and tuition fee waivers based on academic performance, financial need, or specific criteria relevant to applicants.

Students may also seek funding through external organizations, private foundations, and international bodies that support students in engineering and computer science disciplines. Part-time employment is another common way for students to finance their studies, with opportunities available both on campus and in the surrounding Vienna area. It's important for prospective students to investigate the specific eligibility criteria, application procedures, and deadlines associated with these funding options to ensure timely application.

Furthermore, students may explore loan programs available to students in Austria and internationally, which can provide supplemental financial support. The university’s international office and student services offer guidance on financial planning and advise on funding opportunities tailored to individual circumstances. International students should also check for any country-specific scholarships or funding schemes that may be available through their home countries or bilateral agreements.

The university’s transparency in setting tuition fees, which are typically competitive and transparent, helps students plan their finances accordingly. International students often pay higher tuition fees, but these are balanced by the availability of scholarships and external funding options. It is highly recommended that students begin exploring financing options early in their application process to maximize their chances of securing funding. Overall, the combination of university scholarships, government grants, external funding, and personal employment opportunities provides a comprehensive framework to support students financially during their study of Computational Intelligence at the Vienna University of Technology.

The Master's Degree Program in Computational Intelligence at the Vienna University of Technology (TU Wien) offers a comprehensive curriculum designed to equip students with advanced knowledge and skills in the field of artificial intelligence, machine learning, and intelligent systems. The program emphasizes both theoretical foundations and practical applications, preparing graduates for research, development, and innovative tasks in academia and industry. Students have the opportunity to engage with cutting-edge topics such as neural networks, evolutionary algorithms, fuzzy systems, data mining, and pattern recognition, among others. The program is structured to include coursework, research projects, and possibly internships, fostering a multidisciplinary approach that combines computer science, mathematics, and engineering principles.

The program is tailored for students with a background in computer science, electrical engineering, or related fields, and it aims to deepen their understanding of computational methods used for modeling, analyzing, and solving complex problems. As part of the curriculum, students may have access to state-of-the-art laboratories and research groups specializing in intelligent systems, machine learning, and data science. The close collaboration with industry partners and research institutions in Vienna enriches the educational experience, providing practical insights and employment pathways. Graduates of this program are well-prepared to pursue careers in technological development, research institutions, or continue with doctoral studies. The university fosters an international environment, welcoming students from diverse backgrounds and promoting cross-cultural academic exchange. The language of instruction is primarily English, and students can benefit from the university's strong links to the European and global technology sectors.