A student who graduates from the Artificial Intelligence Engineering Department will receive a "bachelor's degree". This degree indicates the level and quality of the educational program the student has completed. A bachelor's degree is usually awarded after completing a four-year program at a university and indicates that the student has a broad knowledge of the field in which he or she is studying.

The Artificial Intelligence Engineering Undergraduate Program aims to provide students with the theoretical knowledge and practical skills needed in the development and implementation of artificial intelligence systems. In this program, students are expected to take an active role in every stage of artificial intelligence technologies. These stages include problem analysis, artificial intelligence modeling, data processing, algorithm development, testing and optimization processes.

Program Content

The Artificial Intelligence Engineering Undergraduate Program offers a comprehensive curriculum to help students gain expertise in this field. The program provides theoretical courses, laboratory studies and project-based learning opportunities to teach the basic components of artificial intelligence. Students are expected to master the following topics:

Machine Learning: Fundamentals of algorithms, supervised and unsupervised learning.

Deep Learning: Artificial neural networks, convolutional networks, recurrent networks.

Natural Language Processing (NLP): Text analysis, language understanding, language generation.

Computer Vision: Image processing, object recognition, video analysis.

Data Analytics: Data collection, cleaning, visualization and analytical modeling.

Artificial Intelligence Ethics: Ethical principles, data security, social impacts of artificial intelligence.

Program Purpose

The program aims to enable students to specialize in artificial intelligence technologies and:

Develop artificial intelligence-based solutions to real-world problems.

Provide the ability to transform theoretical knowledge into practical applications.

Educate competent individuals in the design, development and management of artificial intelligence systems.

Prepare students for careers in technology companies, research laboratories and academic fields after graduation.

Education Process

The program provides students with an interdisciplinary education through both theoretical and applied courses. Some important courses in the curriculum are:

Mathematics and Statistics (Linear Algebra, Probability Theory)

Programming Languages ​​(Python, Java, R)

Data Structures and Algorithms

Big Data and Cloud Computing

Artificial Intelligence and Machine Learning

Robotics and Autonomous Systems

Artificial Intelligence Application Projects

The Artificial Intelligence Engineering Undergraduate program qualifications have been created to ensure that graduates have the knowledge and skills needed in the field of artificial intelligence. These qualifications determine the competencies that students must gain during the education process and their capacity to perform artificial intelligence engineering applications after graduation.

1. Mathematical and Basic Sciences Competence

Mastering the mathematical (linear algebra, probability, statistics) and basic sciences knowledge required to solve artificial intelligence engineering problems.

The ability to apply this knowledge in data analytics, machine learning, and artificial intelligence models.

2. Basic Artificial Intelligence Engineering Competence

Understanding artificial intelligence concepts, algorithms, and architectures.

Ability to effectively use basic artificial intelligence technologies such as machine learning, deep learning, natural language processing (NLP), and computer vision.

Ability to develop artificial intelligence applications in big data management and cloud computing systems.

3. Interdisciplinary Competence

Ability to understand the integration of artificial intelligence engineering with biotechnology, health, finance, education, automotive, and other disciplines.

Assessing and implementing the potential for collaboration in different disciplines.

4. Analytical and Problem Solving Competence

Analyzing complex engineering problems and developing innovative AI-based solutions to solve them.

Using data analytics and modeling techniques in the problem-solving process.

5. Design and Development Competence

Ability to design, model, test, and optimize AI systems.

Developing scalable and reliable AI solutions for real-world problems.

6. Ethics and Social Responsibility Competence

Understanding the ethical dimensions and social impacts of AI applications.

Using AI technologies within the framework of social responsibility and in accordance with ethical standards.

7. Communication Competence

Presenting AI projects and results effectively, both verbally and in writing.

Being able to communicate effectively in multidisciplinary teams and lead collaborative efforts.

8. Continuous Learning Competence

Following rapid developments in the field of AI and adapting to new technologies.

Being able to continuously improve one's knowledge and skills and gain lifelong learning skills.

9. Teamwork Competence

Being able to collaborate in multidisciplinary teams and work effectively with people from different areas of expertise.

Leading and taking responsibility in team projects.

10. Project Management Competence

Ability to manage the planning, execution, monitoring and evaluation processes of artificial intelligence projects.

Ability to perform time management, resource planning and risk analysis.

11. Professional Development Competence

Acquiring new skills in the artificial intelligence engineering career and evaluating professional development opportunities.

Contributing through academic or sectoral R&D studies.

Achievements of the Program

In line with these competencies, Artificial Intelligence Engineering Undergraduate Program graduates:

Combining theoretical knowledge with practical applications,

Developing innovative artificial intelligence solutions for the needs of society,

Working with an ethical and responsible engineering approach,

Able to lead interdisciplinary projects,

Graduates as competent individuals.

Individuals who graduate from this program have the knowledge, skills and experience to meet the expectations of the local and international business world and academia.

The Artificial Intelligence Engineering Undergraduate Department has a strategic importance in today's rapidly advancing era of digital transformation and technology. For this reason, graduates of the department are faced with a wide range of jobs and are in high demand due to the increasing need in the field of artificial intelligence.

Private Sector

Artificial Intelligence Engineering graduates can be employed in the following areas in the private sector:

Artificial Intelligence Development: Developing artificial intelligence software and applications.

Data Science and Analytics: Creating big data analytics and data-driven solutions.

Machine Learning Expertise: Designing and training machine learning models.

Natural Language Processing (NLP): Developing and implementing language processing algorithms.

Computer Vision: Developing image recognition, object detection and video analysis systems.

Autonomous Systems: Developing autonomous vehicles, robotics and intelligent systems.

Other Industries

Graduates can take part in various artificial intelligence projects in various sectors:

Defense Industry: Autonomous systems, artificial intelligence-supported analyses.

Health Sector: Medical image analysis, diagnostic systems, genetic data analytics.

Finance Sector: Algorithmic trading, risk analysis, fraud detection.

Education Sector: Developing personalized learning platforms.

Entrepreneurship and Start-up Culture

Artificial Intelligence Engineering graduates can become entrepreneurs by establishing their own businesses and start technology start-ups.

Artificial Intelligence-Focused Companies: They can develop their own artificial intelligence-based solutions and products.

Consultancy and Education: They can provide consultancy or education services on artificial intelligence technologies.

Research and Academic Career

They can develop new technologies by participating in research and development (R&D) projects or they can do master's and doctorate with the aim of an academic career.

Universities and Research Centers: Advanced research on artificial intelligence technologies.

Global Companies and Laboratories: Working on international projects with the world's leading artificial intelligence companies.

Future Opportunities

For Artificial Intelligence Engineering graduates, job opportunities are constantly expanding in the world where artificial intelligence technologies are rapidly developing. Many sectors such as technology, health, defense, energy, automotive and agriculture need artificial intelligence experts. Artificial Intelligence Engineering graduates are among the experts who are in high demand in both local and international markets and can lead the technology world of the future. This provides graduates with a significant advantage in the sector.

The student's success in the courses is determined by evaluating the mid-term grades and the final exam grade together.

Mid-term grades consist of quizzes, mid-term exam grades and grades given to homework, applications and practical work depending on the course. In the credit system, the type and weight of mid-term and final evaluations (exams, homework, applications and similar) are reported to the relevant department head by the instructor teaching the course within the first two weeks of the semester and announced to the students by the relevant teaching unit administration. The final evaluation is determined by the instructor teaching the course with one of the following letter grades, taking into account the general success level of all students taking that course.

While the impact of the homework given during the semester on the final grade is 40%, the impact of the final exams at the end of the semester is 60%.

The student must have passed all compulsory and elective courses in the program and must not have a grade of F1, F2 or Z. In this program, the student must have a minimum of 240 ECTS credits and a general grade point average of at least 2.00 out of 4.00.