| 1 | To understand the fundamental concepts of artificial intelligence and provide theoretical knowledge about its basic AI components. |
| 2 | To develop competence in understanding search and optimization techniques in artificial intelligence and applying them to various problems. |
| 3 | To provide the ability to understand concepts such as knowledge representation, inference mechanisms, and expert systems and to apply them to real-world problems. |
| 4 | To provide theoretical knowledge on understanding the fundamental principles of machine learning (supervised, unsupervised, accuracy criteria, etc.) and selecting the appropriate method. |
| 5 | To raise awareness of fundamental deep learning structures (artificial neural networks, feedforward networks, etc.) and to provide the ability to interpret them through example applications. |
| 6 | To raise awareness of the ethics, security, societal impact, and future applications of artificial intelligence and to enable students to critically evaluate AI systems. |