Artificial intelligence MSc
The aim of the program is to train professionals who are able to develop and implement the latest artificial intelligence methods, including deep learning, reinforcement learning, and large language models, and to convert them into systems that can be operated in an industrial environment. Our students learn about generative techniques, machine vision, multimodal and embedded solutions, as well as robotics and embodied AI toolkits.
Why at Neumann Faculty?
- Practice-oriented perspective;
- Outstanding infrastructure with modern AI laboratories and cloud-based resources;
- Extensive network of industry and research contacts, including the HUN-REN Hungarian Research Network;
- Reputable academic community;
- Timeless knowledge: the program keeps pace with technological developments, ensuring that the degree remains valuable in the long term.
Course description
The aim of the programme is to train professionals who understand, develop, and apply artificial intelligence systems, who are able to independently and in teams perform high-level tasks related to the development, creation, implementation, operation, and servicing of artificial intelligence solutions, based on theoretical foundations that ensure the long-term development of their knowledge. During the course, students will become familiar with all the tools that can best meet industrial needs. They will also acquire the collaboration and modeling skills necessary to solve development tasks in their field of application and will be able to perform and coordinate research tasks related to artificial intelligence. Graduates of the program are prepared to continue their studies in doctoral programs.
Curriculum
| Full-time | |
|---|---|
| After 09. 2026. | Curriculum F |
Internship
Professional internship is a mandatory requirement. The professional internship is a project-based internship lasting at least 6 weeks (including 240 certified working hours) and must be completed individually or in a group at a suitable organization or at the higher education institution’s training site.
Physical education
Physical education is a 1-credit subject, which is graded on a three-point scale.
More information: https://tsi.uni-obuda.hu/requirements/
Absolutorium
Conditions for obtaining an absolutorium:
- obtaining the 120 credits required by the curriculum;
- fulfilling the criteria requirements;
- completing the required professional internship;
- no financial obligations.
Final exam
Conditions for being admitted to the final examination:
- obtaining a final certificate (absolutorium);
- a thesis accepted by the examiner.
Degree certificate
Conditions for receiving a diploma:
- successful final exam.
A diploma with honors may be awarded to those who achieve excellent results in all subjects of the final exam, receive excellent grades for their thesis and all rigorous exams, have an average grade of at least 3,51 for all other exams and practical grades, and no grade lower than average and no exam with a failing grade.
Detailed description of the programme
Name of the programme
Artificial Intelligence
Field of the programme
Information Technology (IT)
Language of the programme
english
Programme(s) and duration in semesters, number of contact hours
| Field of training | Number of semesters | Number of contact classes |
|---|---|---|
| part-time course | 4 | 370 |
Number of credits to be accumulated to obtain the degree
120 credit
Educational level and qualification indicated in the degree certificate
- educational level: magister (Master of Science, abbreviated: MSc)
- name of master course: Artificial Intelligence
- qualification: Master in Artificial Intelligence
The technical competences to be acquired
a) knowledge
- is familiar with the data analysis, mathematical, statistical, and ethical concepts necessary for innovative, research-level work in the field of artificial intelligence, particularly in the areas of machine learning, deep machine learning, reinforcement learning, generative models, multi-agent systems, cognition, and human collaboration, which form the basis for lifelong learning and knowledge adaptation in changing industrial environments;
- has outstanding knowledge of current concepts, methods, and theories in artificial intelligence, and is aware of the impact of various boundary conditions (such as real-world conditions, large amounts of data, applications developed for specific human support) on modeling and teaching, which facilitate communication with various industrial, administrative, and other actors, and is familiar with the basic concepts of related fields and selected border areas, as necessary, for effective cooperation with industry and other segments of society;
- acquires a high level of knowledge in the main areas of application of artificial intelligence, such as recognition, recommendation, generative, auxiliary, and similar systems, is familiar with the problems associated with these areas and the main directions of possible solutions, the limitations of the application of related techniques, and has the appropriate knowledge to develop new methods and implement and apply modern methods;
- masters the application of software development processes and technologies aimed at the reliable and efficient creation, deployment, maintenance, and expansion of artificial intelligence methods in an industrial environment, covering the entire software life cycle;
- Is aware of the basic principles of human communication, perception, behavior, and thinking, and accordingly understand the possibilities offered by artificial intelligence for the implementation of effective and natural human-machine interaction systems;
- acquires knowledge of the methods and possibilities of developing explainable and safe artificial intelligence, as well as the advantages and disadvantages of certain methods, which enables the application of artificial intelligence even in safety-critical systems;
- achieves a level of English language proficiency sufficient for training, understanding English-language literature, understanding and processing technical texts, performing professional tasks requiring professional qualifications, and continuous professional self-education;
- is familiar with the basic legal knowledge and laws related to artificial intelligence-based software, data management, and autonomous systems;
- is familiar with artificial intelligence methods that promote ethical use and combat bias, as well as the goals and methodology of human-centered artificial intelligence.
b) skills
- capable of designing, implementing, analyzing, validating, and evaluating artificial intelligence solutions and models, designing, implementing, analyzing, validating, and evaluating models, understand their operation, recognizing and assessing various data/cyber/ethical/operational security challenges affecting artificial intelligence systems, and applying the principles of secure system design;
- able to interpret and resolve complex tasks arising in various industrial environments and specific scientific disciplines using known methods, to separate tasks according to scientific field, and to plan solutions;
- able to recognize and perform routine tasks closely related to the field of artificial intelligence, such as recognition, recommendation, generation, and assistance, which enable rapid application development and prototype production;
- able to understand and, if necessary, perform the preparatory tasks associated with the specified task, such as data collection, data preparation, data analysis, data processing, and data representation;
- able to support the software development life cycle using artificial intelligence, taking into account the possibilities of implementation, training, operation, expansion, development, replacement, and decommissioning;
- is capable of developing systems that meet specific needs, are evolving, personalized, and promote cooperation; their work meets ethical and industrial reliability criteria, as well as the applicable legal framework;
- able to cooperate effectively with a wide range of artificial intelligence users, both in terms of preparation and application possibilities and methods, and able to apply the acquired knowledge in specific areas (e.g., in the health, financial, industrial, educational, or service sectors);
- be able to interpret results in an easily understandable way, both textually and visually; is able to implement customizable systems, thus promoting transparency and multi-purpose usability; is able to conduct professional discussions, present and interpret results, prepare reports, process professional materials, and give presentations in English, in addition to their native language;
- is able to individually extend their knowledge to unfamiliar tasks based on their previous experience using known methods, is able to identify research, development, and innovation directions, define related milestones, and implement them with the appropriate research background.
c) attitude
- monitors the latest developments in artificial intelligence and related fields, primarily in mathematics, statistics, information technology, and other specialized areas, and strives to apply these developments to their own advancement;
- respects and takes into account opinions that differ from their own in their work, and considers only professional arguments to be acceptable means of persuasion;
- represents their profession authentically and presents the results of their work;
- is committed to communicating and implementing environmentally conscious and sustainable behavior;
- is committed to the ethical use of artificial intelligence and overcoming prejudice in line with the objectives of human-centered artificial intelligence.
d) their autonomy and responsibility
- pays close attention to the precise performance of tasks and strict adherence to deadlines, and ensures that others do the same;
- independently performs routine recognition, recommendation, generation, and auxiliary system design tasks, both individually and as a member or leader of a group;
- takes responsibility for the work of those working with or under their supervision;
- handles sensitive and potentially confidential data entrusted to them responsibly and in accordance with current regulations;
- performs their work with the utmost consideration for professional and scientific ethical requirements.
Main areas of the course
| Area | Credit |
|---|---|
| Mathematics and natural sciences | 10-20 |
| Computer science and artificial intelligence core curriculum | 20-30 |
| Knowledge resulting in special competencies in the field of artificial intelligence | 40-50 |
| Elective courses and Thesis | 30-40 |
