Unique opportunity in Hungary
The Faculty of Informatics of the University of Debrecen offers a 1-year (2 semesters) advanced training course in Artificial Intelligence (AI Expert) in English in a hybrid format. During the course, participants will learn modern AI-based data processing methods in a university environment and will be able to create and operate IT solutions using artificial intelligence. Currently, such training course is only offered by the Faculty of Informatics of the University of Debrecen in Hungary.
Who is it recommended for?
The aim of the course is to provide high-level, state-of-the-art training in artificial intelligence for those who already have a basic IT knowledge. The training will be useful for the younger generation of newcomers to the profession as well as for those who have not yet had the opportunity to learn about these tools in the last decades during their studies. Our aim is to train professionals who can develop state-of-the-art applications using artificial intelligence, both offline and in the cloud, using the latest technological processes.
To ensure the global nature and measurability of the training, participants can optionally obtain industry certifications, notably NVIDIA (the current list can be found here: Nvidia Deep Learning Institute - Debreceni Egyetem) and Microsoft (e.g. Azure Fundamentals, Azure AI Fundamentals, Azure AI Solution, Azure AI Engineer Associate). The list of certificates available at the Faculty is constantly expanding, following international trends and technological developments. The Faculty of Informatics is the official Hungarian examination center of Certiport, the leading provider of certification exam development.
The courses and their contents have also been designed to overlap as much as possible with the industry certifications. The preparatory courses integrated into the training will thus enable students to obtain international industry certificates in a supervised examination environment at the international examination center of the Faculty of Informatics, but also optionally at other locations, and will allow graduates to add further certificates to their professional portfolio in addition to the certificate of completion of the specialized training.
The list of courses (532 hours in total: 196 hours of lectures, 336 hours of laboratory/exercise):
- Machine learning
- Data protection and cryptography
- Generative methods
- Parallel computing
- AI programming
- Autonomous vehicles
- Efficient data visualization
- Cloud computing
- Reinforcement learning
- Image processing based on neural networks
- Natural language processing and text mining
- AI frameworks
- Big Data handling techniques
- Thesis work
The training courses are taught by qualified trainers who are experts in their field.
Dr. András Hajdu, Professor, responsible for the course, Department of Data Science and Visualisation
Dr. Attila Adamkó Associate Professor, Department of Information Technology
Dr. Bernadett Aradi Assistant Professor, Department of Applied Mathematics and Probability Theory
Dr. Ágnes Baran Associate Professor, Department of Applied Mathematics and Probability Theory
Dr. Sándor Baran Professor, Department of Applied Mathematics and Probability Theory
Dr. Tamás Bérczes Associate Professor, Department of Information Systems and Networks
Dr. Zoltán Gál Associate Professor, Department of Information Systems and Networks
Dr. Balázs Harangi Associate Professor, Department of Data Science and Visualisation
Dr. Márton Ispány Associate Professor, Department of Information Technology
Dr. László Kovács Assistant Professor, Department of Data Science and Visualisation
Dr. Kinga Kruppa Assistant Professor, Department of Data Science and Visualisation
Dr. Roland Kunkli Assistant Professor, Department of Data Science and Visualisation
Dr. Andrea Pintér-Huszti Associate Professor, Department of Computer Science
Dr. László Szathmáry Associate Professor, Department of Information Technology
Dr. Henrietta Tomán Assistant Professor, Department of Data Science and Visualisation
Dr. Ádám Tóth Assistant Professor, Department of Information Systems and Networks
Why is this training unique?
The training, which can be followed also online, takes place in the classrooms of the Faculty of Informatics. The following teaching services are also included in the tuition fee:
- cloud credits required to complete the course for labs held in the cloud (e.g. Microsoft Azure),
- the possibility of attending additional training courses for industry certifications offered by the Faculty of Informatics,
- one-time exam opportunities to collect industrial certificates in connection with certain courses (only if you use the Faculty's exam center).
The completed courses are accepted for the 2-years Data Science MSc at the Faculty of Informatics. In particular, the completion of the Data Science MSc can be significantly shortened by up to 1 year in this way.
Opportunities after completing the training
The following jobs are available after the training:
- AI Developer
- Application Developer
- Big Data Developer
- Data Architect
- Data Analyst
- Data Engineer
- Data Engineering Manager
- Data Platform Specialist
- Data Scientist
- Data Science Developer
- Data Science Manager
- Digital Business Data Analyst
- It Security Research Engineer
- Lead Data Engineer
- Lead Data Scientist
- Logistics Process Engineer
- Machine Learning Engineer
- Machine Learning Specialist
- Marketing Data Analyst
- Staff Data Engineer
The preparation and launch of the training was supported by several industrial partners, including Bosch, EPAM, General Electric, Microsoft, NI, NVIDIA.
Start date: February 2024 
Duration of training: 1 year (2 semesters)
Language of training: English
Entry requirement: Bachelor/Master degree in Computer Science, Conputer Science Engineering or Business Informatics
Delivery: hybrid (face-to-face and online attendance possible, exam with face-to-face attendance only)
Tuition fee: 8,000 USD/semester
Application fee: 150 USD
Deadline for application: 15 January 2024 
Decision on the start of the course and successful admission: 31 January 2024 
I am interested in the training
Please submit your application by clicking on the Registration button at the bottom of the page.
(Click on the link to apply! ↑)
 Expected start date. A minimum number of students is a prerequisite for starting the course. Admission to the course is not automatic; if necessary, the number of applicants can be maximised and the ranking of applicants may influence the success of the application. We reserve the right to make changes to the details of the course, such as launch, admission, starting date, etc.