Geri
A-Z İndex
Student Affairs
Life At Haliç
| Academic | Institues | Institute of Graduate Studies | Departments | Artificial Intelligence Engineering|
Master's Degree Program in Artificial Intelligence Engineering without Thesis, Bachelor's Degree Program in Artificial Intelligence Engineering, Computer Engineering, Software Engineering, Electrical and Electronics Engineering, Mathematics, Statistics, or other relevant programs specified in the admission requirements. The program focuses particularly on sectoral specialization and professional competency acquisition. It aims to develop students' abilities to generate solutions to industrial problems, manage data-driven decision-making processes, and design and implement artificial intelligence systems. Students have the opportunity to specialize in areas such as machine learning, deep learning, natural language processing, computer vision, data mining, big data analytics, optimization, artificial intelligence-based decision support systems, and autonomous systems. The courses included in the program are application and project-based, enabling students to develop solutions by working on real-world scenarios. At the end of the program, students demonstrate the knowledge and skills they have acquired through a Term Project prepared under the guidance of an advisor. |
Akademik kadro bilgileri şu anda yüklenemiyor. Lütfen daha sonra tekrar deneyiniz.
| Haliç University Department of Artificial Intelligence Engineering Non-Thesis Master's Program began education and training in the 2025-2026 academic year. |
| Students who successfully complete the program are awarded a Master's Degree in Artificial Intelligence Engineering (Thesis-Free). |
| You must have completed your undergraduate education in Engineering or in one of the basic science fields involving mathematics, such as Management Information Systems, Mathematics, Physics, and Statistics. |
| Students who graduate from a non-thesis master's program may apply to thesis-based master's programs or integrated doctoral programs if they meet the necessary requirements according to the relevant legislation. |
| Ders Kodu | Ders Adı | T+U+L | AKTS | Ders Türü |
|---|---|---|---|---|
| LÜE8000 | Scientific Research Methods and Publication Ethics | 3+0+0 | 6 | Compulsory |
| AİS1XX1 | Area Elective Course 1 | 3+0+0 | 6 | Elective |
| BİM8160 | Embedded Systems | 3+0+0 | 6 | Elective |
| BİM8290 | Deep Learning | 3+0+0 | 6 | Elective |
| BİM8330 | Data Mining | 3+0+0 | 6 | Elective |
| BİM8480 | Optimization Theory | 3+0+0 | 6 | Elective |
| BİM8520 | Pattern Recognition | 3+0+0 | 6 | Elective |
| BİM8530 | Database Systems | 3+0+0 | 6 | Elective |
| BİM8570 | Graph Theory and Algorithms | 3+0+0 | 6 | Elective |
| YZM8110 | Statistical Data Analysis | 3+0+0 | 6 | Elective |
| YZM8120 | Statistical Learning | 3+0+0 | 6 | Elective |
| YZM8130 | Big Data Analytics | 3+0+0 | 6 | Elective |
| YZM8140 | Machine Learning | 3+0+0 | 6 | Elective |
| YZM8150 | Reinforcement Learning | 3+0+0 | 6 | Elective |
| YZM8160 | Hybrid Machine Learning Models | 3+0+0 | 6 | Elective |
| YZM8170 | Optimization Techniques for Artificial Intelligence | 3+0+0 | 6 | Elective |
| YZM8180 | AI Systems Design | 3+0+0 | 6 | Elective |
| YZM8190 | Software Engineering for AI Systems | 3+0+0 | 6 | Elective |
| YZM8210 | Federated Learning | 3+0+0 | 6 | Elective |
| YZM8220 | Artificial Intelligence and Ethics | 3+0+0 | 6 | Elective |
| YZM8230 | Natural Language Processing | 3+0+0 | 6 | Elective |
| YZM8240 | Computer Vision | 3+0+0 | 6 | Elective |
| YZM8250 | Image Processing | 3+0+0 | 6 | Elective |
| YZM8260 | Digital Signal Processing | 3+0+0 | 6 | Elective |
| YZM8270 | Advanced Digital Signal Processing | 3+0+0 | 6 | Elective |
| YZM8280 | Robotics | 3+0+0 | 6 | Elective |
| YZM8290 | Autonomous Mobile Robots | 3+0+0 | 6 | Elective |
| YZM8310 | Artificial Intelligence in Medical Sciences | 3+0+0 | 6 | Elective |
| YZM8320 | Artificial Intelligence in Finance | 3+0+0 | 6 | Elective |
| YZM8330 | AI in Cybersecurity | 3+0+0 | 6 | Elective |
| YZM8340 | Game Theory | 3+0+0 | 6 | Elective |
| YZM8350 | Cloud Computing | 3+0+0 | 6 | Elective |
| Ders Kodu | Ders Adı | T+U+L | AKTS | Ders Türü |
|---|---|---|---|---|
| AİS1XX2 | Area Elective Course 1 | 3+0+0 | 6 | Elective |
| Ders Kodu | Ders Adı | T+U+L | AKTS | Ders Türü |
|---|---|---|---|---|
| YZM7000 | Term Project | 0+0+0 | 30 | Compulsory |
| Students must take 9 elective courses, Scientific Research Methods and Publication Ethics, and a term project course. A total of 90 ECTS credits must be earned. |
|
Program graduates can work in public and private sector organizations operating in the fields of artificial intelligence, data science, and smart systems. Graduates can work as specialists or project developers in technology companies, banks, financial institutions, defense industry, health technology companies, telecommunications companies, e-commerce companies, and R&D centers. Graduates can take on positions such as data analyst, data scientist, machine learning engineer, artificial intelligence developer, business intelligence specialist, and big data analyst. |
|
Students' academic performance is determined in accordance with the provisions of the Haliç University Graduate Education and Teaching Regulations. |
| Associate Prof.Dr. Ülviye HACIZADE |
| Enstitü Sekreteri Buse AKYILDIZ |
