The academic content of the Bachelor of Science in Artificial Intelligence and Data Engineering is designed to provide students with a solid grounding in core areas such as computer science, mathematical modeling, algorithm design and data analysis. The program's curriculum comprehensively addresses the theoretical and applied aspects of artificial intelligence and data science.
In the first years of the program, students are introduced to the basics of computer science, programming languages (usually Python, Java, etc.), data structures, algorithms, basic electronics and mathematics. In addition, analytical thinking skills are developed through courses based on mathematical foundations such as statistics and probability theory.
In later semesters, artificial intelligence concepts are covered in more detail. Special courses in areas such as machine learning, deep learning, artificial neural networks, natural language processing and computer vision are an integral part of the program. Students are introduced to data mining techniques and big data technologies, giving them the necessary skills for data-intensive applications.
The hands-on aspect of the program is also strong. Laboratory work, project-based learning and real-time data analysis projects provide students with the opportunity to practice and apply what they have learned to real-world problems. Students learn to put their theoretical knowledge into practice through research projects and software development workshops offered within the curriculum.
Ethical and societal dimensions are also taken into account, focusing on issues such as the impact of artificial intelligence on society, data privacy and security. Such courses help students understand the societal responsibilities of technology and act in an ethical manner.
As a result, the curriculum of the Artificial Intelligence and Data Engineering program provides students with not only technical and theoretical knowledge, but also all the necessary tools to become sought-after professionals in the industry, equipped with ethical, societal and practical skills. This holistic educational approach ensures that graduates are able to create innovative solutions to complex data problems.