|Study location||Hungary, Győr|
|Type||Master, full degree studies|
|Nominal duration||4 semesters (120 ECTS)|
|Course code||Computer Science and Information Technology|
Bachelor diploma (or higher)
Bachelor’s Degree in Computer Science or a related field. Decision regarding admission is based on individual assessment of the applicant’s preliminary qualifications.
The entry qualification documents are accepted in the following languages: English / Hungarian.
Often you can get a suitable transcript from your school. If this is not the case, you will need official translations along with verified copies of the original.
You must take the original entry qualification documents along with you when you finally go to the university.
We can accept admission documents in Hungarian, English or notarized English translations.
The programme brings its active and motivated students to professional level in artificial intelligence, digital twins (computational modelling with automated data coupling), and high performance computing. The programme prepares the students to scientific research and innovations in international research and innovation teams, development and research work in industry, and/or professional work in industry and other sectors
We use the central admission system with the support of the Center for International Programs:
1. review of the language and academic test with the help of the INOK and the head of the programme,
2. evaluating the previous academic results and admission documents
4. Online interview for students (including oral language test where language skills are not clear based on the certificates submitted
5. Verification of formal requirements
Dr. Harmati István
The degree requires acquisition of 120 credits, where 1 credit equals one ECTS credit, and 1 credit is defined as 25 working hours.
The courses of the programme are divided into three categories:
• compulsory courses on mathematics (17 credits), data science (14 credits), programming and HPC (22 credits)
• compulsory courses on research methodology (2 credits) and master’ thesis preparation (30 credits)
• electives in mathematics (15 credits), data science (5 credits) and programming (25 credits) among which 5 courses are mandatory to select (25 credits)
• freely elected courses from a selected set of courses of the university (10 credits)