Study programme

Basic information

Study programme in national registry:
Guaranted by: Faculty of Electrical Engineering and Informatics
Study field: Computer Science
Level of degree: 1
Form of study: present
Degree: Bc.
Length of study in years: 3
Professionally oriented: No
Joint study programme: No
Languages of delivery:

Graduate profile

Description
The Artificial Intelligence (AI) study programme is a modern, technology-oriented and application-oriented first-cycle study programme designed to educate professionals capable of designing, implementing, and integrating AI-based systems across a wide range of application domains. The programme builds upon the existing Intelligent Systems and Business Informatics study programmes and extends them with new, up-to-date courses in artificial intelligence, data science, natural language processing, generative AI, computer vision, AI ethics, robotics, and intelligent systems. The curriculum combines computer science, mathematics, and information technologies, with a strong emphasis on hands-on projects and the development of competencies required for the digital economy, including the effective and ethical use of generative AI. Graduates acquire a comprehensive profile that integrates computing, data science, and ethical competencies aligned with the latest developments in artificial intelligence, as well as the requirements of Industry 5.0 and a digitalized society.
Learning objectives
The educational objectives integrate selected strategic goals of the Technical University of Košice, the strategic goals of the Faculty of Electrical Engineering and Informatics of the Technical University of Košice, the requirements of employers, the Qualifications Framework of the European Higher Education Area (EHEA), and the National Qualifications Framework. The objective of the Artificial Intelligence study programme is to educate graduates who are capable of understanding, analysing, and designing intelligent systems based on artificial intelligence, machine learning, and data science methods, and of applying these technologies ethically and responsibly to address practical and societal challenges. The programme is designed to ensure that graduates: - acquire systematic knowledge of computer science, mathematics, statistics, and the fundamentals of artificial intelligence, building upon secondary school knowledge while extending it with modern AI concepts; - are able to apply this knowledge professionally to solve real-world problems, design and implement machine learning models, work with data, and use state-of-the-art software and cloud-based tools; - are capable of independently analysing and interpreting data, making evidence-based decisions, and applying data visualisation and analytical methods to communicate results effectively; - understand the broader context of artificial intelligence, including its ethical, legal, and societal implications, the FAIR principles, and the responsible use of AI technologies; - develop transferable skills such as teamwork, project management, presentation skills, and the ability to communicate technical concepts effectively to both specialist and non-specialist audiences; - gain practical experience through projects that integrate knowledge from multiple domains, including AI applications in cloud computing, data analytics, the Internet of Things (IoT), Industry 5.0, robotics, transportation systems, and healthcare; - demonstrate the ability to engage in independent learning, adapt to emerging technologies, and continuously develop their knowledge and professional competencies throughout their careers.
Main learning outcomes
Graduates of the Bachelor's study programme in Artificial Intelligence possess professional knowledge in computer science, mathematics, statistics, data science, robotics, intelligent systems, and the fundamentals of artificial intelligence. They understand the core principles of machine learning, neural networks, fuzzy systems, optimization methods, natural language processing, computer vision, and generative AI. They are able to analyse problems, select appropriate artificial intelligence methods, and implement solutions in specific technological environments. Graduates are capable of working with various types of data, including structured, textual, image, and sensor data, and of using modern tools for data processing, visualization, and their application in prediction, diagnostics, and control. They demonstrate the ability to work independently, think creatively, and collaborate effectively within multidisciplinary teams. They are prepared to contribute to projects involving the development and deployment of intelligent systems in areas such as industrial automation, robotics, healthcare, transportation, smart technologies, energy, and services. Graduates understand the broader societal implications of artificial intelligence and are able to consider these aspects when making decisions and communicating with stakeholders. They possess well-developed competencies for continuous professional development and lifelong learning, enabling them either to continue their studies in a second-cycle (Master's) programme or to pursue a professional career in industry and research. Graduates combine technical and analytical skills with an ethical and critical approach to the development and application of artificial intelligence, making them adaptable professionals well prepared for employment in the modern digital society. Typical career opportunities include: - AI and machine learning solution developer; - data analyst or specialist in data processing and predictive modelling; - software developer, research engineer, or technical specialist in the field of intelligent systems; - member of multidisciplinary teams developing and deploying AI solutions in industry, services, the public sector, or start-ups.
Professions
Professions for which the graduate is prepared at the time of completion.

Employability

Evaluation of the study programme graduates employability
Not applicable, as this is a newly proposed study programme. The proposed Artificial Intelligence study programme will replace the existing Intelligent Systems and Business Informatics study programmes, whose graduate employment rates have ranged between 84.8% and 97% in recent years. More detailed information for the years 2018 and 2019 is available on the https://uplatnenie.sk Typical career opportunities include: - AI and machine learning solution developer; - data analyst or specialist in data processing and predictive modelling; - software developer, research engineer, or technical specialist in the field of intelligent systems; - member of multidisciplinary teams developing and deploying AI solutions in industry, services, the public sector, or start-ups.
Evaluation of the study programme quality by employers
Statements provided by: - Ing. Martin Džbor, PhD, MBA – Deutsche Telekom IT Solutions Slovakia, Strategy & Technology Officer - Ing. Ján Majoroš, MBA – Siemens Healthineers Slovakia, Head of Offensive Security Testing

Structure and content of the study programme

Suggested study plan in the MIAS portal

Current academic year plan and current schedule

Current academic year plan
Current schedule: MAIS portal

Persons responsible for the study programme

Person responsible for thequality of the study programme: doc. Ing. Peter Papcun, PhD.
List of persons responsible for the profile courses: Study advisor: Ing. Ján Magyar, PhD.
Student representatives: Dominik Beluško
Study department

Spatial, material, and technical provision of the study programme and support

List and characteristics of the study programme classrooms
List and description of classrooms and laboratories: https://uui.fei.tuke.sk/sk/odborne-laboratoria The above-mentioned laboratories provide access to the supporting technical and software infrastructure developed and operated by the Institute of Artificial Intelligence, Faculty of Electrical Engineering and Informatics, consisting of: A private cloud computing cluster comprising 10 servers with a total capacity of 156 CPU cores and 724 GB of RAM, storage capacity exceeding 6 TB, and shared storage space of more than 100 TB. The infrastructure also includes servers equipped with GPUs for high-performance computing (TESLA K-40c, Quadro RTX 4000, and Quadro P4000). The integrated DataLab cloud environment for research and education, providing tools for data analytics and big data processing technologies, including database storage as well as frameworks for distributed computing and deep learning: https://datalab.kkui.fei.tuke.sk University Science Park TECHNICOM (https://uvptechnicom.sk/sk): Start-up Centre, Business Incubator, Business Acceleration Services. University Library (http://www.lib.tuke.sk/): Conference facilities for lectures and events organized in cooperation with industrial partners, such as conferences, hackathons, workshops, and similar activities.
Characteristics of the information provision
Access to study literature and information databases is provided through the Technical University of Košice University Library: https://www.lib.tuke.sk/#/digitalLibrary Access to information technologies and IT services is provided by the University Computing Centre of the Technical University of Košice: https://uvt.tuke.sk/sk/kms A server rack comprising five servers (4× IBM: 8 cores, 8 GB RAM each; 1× HPE: 10 cores, 16 GB RAM; 2× disk arrays with a total capacity of 5 TB) is located in room V012 at Vysokoškolská 4. The server infrastructure is used to support teaching activities, final thesis projects, the collection and processing of data from the models described in Section (a), the storage and sharing of teaching materials, and the hosting of promotional websites for the study programme. In addition, the Institute operates the following infrastructure to support its activities and the associated teaching: 1. A private cloud computing cluster consisting of 10 servers with a total capacity of 156 CPU cores and 724 GB of RAM, storage capacity exceeding 6 TB, and shared storage space of more than 100 TB. The infrastructure includes servers equipped with GPUs for high-performance computing (TESLA K-40c, Quadro RTX 4000, and Quadro P4000). 2. An integrated DataLab cloud environment for research and education, providing tools for data analytics and big data processing technologies, including database storage as well as frameworks for distributed computing and deep learning.
E-learning
Study materials are available through software platforms supporting educational activities and collaborative learning, such as Microsoft Teams and the Moodle e-learning platform. Lectures, practical classes, and consultations with students are also conducted through the CISCO Webex communication platform. Access to these tools is provided free of charge to both TUKE employees and students. https://www.fei.tuke.sk/sk/bakalarske-studium
Institution partners
The following partners will participate in ensuring educational activities within the Bachelor’s study programme in Artificial Intelligence: - U.S. Steel Košice s.r.o.: guest lectures in selected courses, a joint laboratory at TUKE and the Institute of Artificial Intelligence, and industry-oriented projects; - Siemens Healthcare s.r.o.: consultation of final theses, a joint laboratory at TUKE, and joint research projects; - Deutsche Telekom IT Solutions Slovakia: development of transferable competencies – verbal and non-verbal communication (seminar), transferable competencies – time management (seminar); - BSH Drives and Pumps s.r.o.: guest lectures in selected courses, consultation of final theses; - Betamont s.r.o.: joint research projects; - Microsoft Slovakia s.r.o.: guest lectures in selected courses, joint projects; - IBM Slovensko s.r.o.: guest lectures in selected courses, joint projects, acquired innovation projects, academic education and research programmes; - Siemens, s.r.o.: guest lectures in selected courses, work with hardware, firmware, and software in laboratories; - ControlSystem s.r.o.: guest lectures in selected courses, work with hardware, firmware, and software in laboratories; - KYBERNETES s.r.o.:transferable competencies, consultation of final theses; - Ewon; - Pantek, Aveva, Wonderware; - Rockwell Automation.

Admission procedures

Required abilities and necessary admission requirement
Admission procedures
Results of the admission process over the last period

Additional informtation

Additional informtation on department's web