The aim of this course is to introduce students to the basic concepts, algorithms and application areas of artificial intelligence and to enable them to develop applications.

This course provides a comprehensive introduction to artificial intelligence (AI), covering a wide range of topics from its basic concepts to its modern applications. Throughout the course, students will lay the foundations of AI with problem-solving and search algorithms, and learn how systems reason with knowledge representation and logic. Focusing on machine learning, critical steps such as data preprocessing, feature extraction and selection, and data normalization will be detailed, and both supervised learning (regression, classification) and unsupervised learning (clustering) algorithms will be examined. In addition, advanced topics such as pattern recognition and swarm intelligence will be covered, and the principles of artificial neural networks and deep learning (CNN, RNN) and their applications in natural language processing will be understood.