ECTS Information Package / Course Catalogue
HOME INSTITUTIONAL INFORMATIONINFORMATION ON DEGREE PROGRAMMES Artificial Intelligence Engineering (in English)CERTIFICATE PROGRAMMESUSEFUL INFORMATION, RESOURCES & SERVICES FOR STUDENTSUSEFUL LINKS AND DOCUMENTSADITIONAL & SUPPORTING INFORMATION
- About Beykoz University
- Mission, Vision & Core Values
- Education Model
- Institutional Learning Outcomes (ILOs)
- University Common Courses
- Academic Calendar
- List of Programmes Offered
- Admission & Registritaion
- Credit Transfer And Recognition Of Prior Learning
- ECTS Credit Allocation
- Academic Counselling And Monitoring For Student Achievement
- Language Policy
- Diploma, Diploma Supplement & Europass Documents
ARTIFICIAL INTELLIGENCE ENGINEERING (IN ENGLISH) BACHELOR`S (FIRST CYCLE) DEGREE PROGRAMME |
|||||
|---|---|---|---|---|---|
| Level of Qualification & Field of Study | |||||
Bachelor's (First Cycle) Degree |
4 |
240 |
Full Time |
|
|
PROGRAMME PROFILE |
Beykoz University’s Bachelor’s Program in Artificial Intelligence Engineering (English) is a four-year undergraduate program consisting of 240 ECTS credits. It is structured at Level 1 of the Framework for Qualifications of the European Higher Education Area (QF-EHEA) and at Level 6 of the Turkish Qualifications Framework and the Turkish Higher Education Qualifications Framework. The program has been designed in line with Beykoz University’s engineering education approach, which emphasizes application, technology, competency development, and adaptation to the changing world of work.
The program aims to educate engineers who possess strong theoretical and practical knowledge in mathematics, programming, data management, software development, and artificial intelligence; who can analyze real-world problems, select appropriate AI methods, and transform these methods into products, systems, and services. Ethics, security, reliability, privacy, and the responsible use of artificial intelligence are addressed as fundamental components of the program.
In addition to mathematical and computational foundations, students receive education in programming, data structures and algorithms, data analytics, machine learning, deep learning, natural language processing, large language model applications, vector databases and embedding systems, AI product development, backend development, cloud technologies, MLOps, security, web and mobile integration, AI agents, and workflow automation. In this way, students gain a holistic engineering perspective that addresses artificial intelligence not only at the model-development level, but also through data, software, integration, deployment, monitoring, and product life-cycle dimensions.
The application-oriented structure of the program is supported by projects, laboratory studies, product development activities, and industry-based work. Before graduation, students are expected to gain experience in working on real-world problems and in designing, developing, evaluating, and improving AI-enabled products and systems. The program also aims to develop competencies in teamwork, technical communication, problem solving, project management, entrepreneurship, ethical awareness, and lifelong learning.
Program field and level codes: [PENDING CONFIRMATION]
The program aims to educate engineers who possess strong theoretical and practical knowledge in mathematics, programming, data management, software development, and artificial intelligence; who can analyze real-world problems, select appropriate AI methods, and transform these methods into products, systems, and services. Ethics, security, reliability, privacy, and the responsible use of artificial intelligence are addressed as fundamental components of the program.
In addition to mathematical and computational foundations, students receive education in programming, data structures and algorithms, data analytics, machine learning, deep learning, natural language processing, large language model applications, vector databases and embedding systems, AI product development, backend development, cloud technologies, MLOps, security, web and mobile integration, AI agents, and workflow automation. In this way, students gain a holistic engineering perspective that addresses artificial intelligence not only at the model-development level, but also through data, software, integration, deployment, monitoring, and product life-cycle dimensions.
The application-oriented structure of the program is supported by projects, laboratory studies, product development activities, and industry-based work. Before graduation, students are expected to gain experience in working on real-world problems and in designing, developing, evaluating, and improving AI-enabled products and systems. The program also aims to develop competencies in teamwork, technical communication, problem solving, project management, entrepreneurship, ethical awareness, and lifelong learning.
Program field and level codes: [PENDING CONFIRMATION]