Faculty of Computer and Infomation Sciences | Artificial Intelligence And Machine Learning Pr. (English)

Profile of the Programme

The Department of Artificial Intelligence and Machine Learning is an undergraduate program that aims to educate individuals with theoretical knowledge and practical skills in artificial intelligence and machine learning, who can keep up with technological developments and develop solutions to problems across different disciplines. The program aims to provide students with a foundation in mathematics, computer science, and data analysis, enabling them to apply their knowledge to artificial intelligence applications.

The curriculum is structured around fundamental subjects such as mathematics, linear algebra, probability, statistics, computer programming, data structures, algorithms, database management, and optimization. Students are expected to use this foundation to understand and apply methods such as machine learning, deep learning, and artificial neural networks. Emphasis is also placed on developing knowledge and skills in data collection, data preprocessing, model development, model training, and performance evaluation.

Throughout the educational process, theoretical knowledge is supported by programming exercises and project-based activities. The program aims to develop students' competencies in problem identification, algorithm selection, software development, model evaluation, and optimization. In addition, emphasis is placed on teamwork, project management, analytical thinking, technical communication, and professional ethics. The program seeks to educate individuals who are aware of the impacts of artificial intelligence technologies on individuals and society and who consider data privacy, reliability, and ethical principles in their work.

The language of instruction of the program is 100% English. This supports students in following international scientific publications, technical resources, and current technological developments, communicating with experts from different disciplines, and continuously improving their professional knowledge and skills.

The program aims to equip graduates with the knowledge and skills required to pursue careers in artificial intelligence, machine learning, data science, and software development in public institutions, private sector organizations, technology companies, and R&D centers.

To visit the website of the Department of Artificial Intelligence and Machine Learning, please click here.

Programme Director & ECTS Coord.

DEPARTMENT CHAIR
DR.ÖĞR. ÜYESİ NİHAL İNCE
DR.ÖĞR. ÜYESİ NİHAL İNCE

Specific Admission Requirements

General admission requirements stated under Info on the Institution on this website are being applied to start this programme.

Recognition of Prior Learning

Depending on the degrees awarded, theoretical or practical courses taken as part of a degree (completed or not completed) may lead to recognition of these as prior learning by the programme administration. The students who have taken courses in another institution in Turkey or abroad can ask for credit and grade transfer. The executive boards of relevant programme will decide on the courses to be transferred covering students' entire academic program once and for all with the condition that the request for transfer be made within the first week of the academic year, the requests cannot be repeated.

Qualification Requirements and Regulations

A student is required to successfully complete the designated program of courses meet a minimum of 240 ECTS credit requirement and have a minimum GPA of 2.00/4.00 and no FF, DZ or YZ grades.

Access to Further Studies

May apply to master's or doctorate programmes in any field or proficiency in fine arts programmes

Graduation Requirements

A student is required to successfully complete the designated program of courses meet a minimum of 240 ECTS credit requirement and have a minimum GPA of 2.00/4.00 and no FF, DZ or YZ grades.

Occupational Profiles of Graduates

Graduates of the Department of Artificial Intelligence and Machine Learning have employment opportunities in various sectors, including software and technology companies, R&D centers, finance and banking, healthcare, defense, automotive, manufacturing, telecommunications, education, and public institutions.

Our graduates may work in fields such as artificial intelligence, machine learning, data science, deep learning, data analytics, natural language processing, computer vision, and intelligent systems development. They may also take part in developing AI-based software solutions, analyzing data, building predictive models, and integrating artificial intelligence technologies into existing systems.

The main professional positions available to graduates include:

Artificial Intelligence Specialist
Machine Learning Engineer
Data Scientist
Data Analyst
AI Software Developer
Deep Learning Specialist
Natural Language Processing (NLP) Specialist
Computer Vision Specialist
Artificial Intelligence R&D Specialist
Machine Learning Operations (MLOps) Specialist

In addition, they may pursue academic careers through graduate studies, participate in scientific research and development activities, or engage in entrepreneurial activities in the field of artificial intelligence.

Examination Regulations, Assessment and Grading

A variety of assessment methods such as mid-term(s), assignment(s), exercise(s), project(s), practice(s), and a final exam are implemented in the programme. Assessment methods may include classical test(s), multiple-choice test(s), homework(s), performance evaluation(s), and product evaluation(s). In order to graduate from the programme, cumulative GPA must be minimum 2.00. A course grade is constituted by evaluating the above stated elements and given by using letters. Letter grades and their associated coefficients are as follows;

Grade	Coefficient
AA	4,0
AB	3,7
BA	3,3
BB	3,0
BC	2,7
CB	2,3
CC	2,0
CD	1,7
DC	1,3
DD	1,0
FF	0,0