Artificial intelligence is a sub-field of computer science that deals with the design and development of computer systems that possess characteristics (ability to solve problems, represent knowledge, infer, learn, etc.) that are related to the intelligence in human behaviour. Today, the development of artificial intelligence methods, technologies and applications is very rapid: self-driving vehicles, chatbots, product recommendation systems, news bots, virtual assistants, neural network-based medical diagnosis, emotionally intelligent tutoring systems, and impressive industrial robots. Such a rapidly growing role of artificial intelligence in the modern and future society emphasizes the demand for academically educated professionals who have mastered the fundamentals of artificial intelligence, know its perspectives, and have experience in solving artificial intelligence tasks to deal with a variety of problems facing engineers, designers, financial professionals, educators and medical staff, etc. This study course focuses on the construction of a state space graph of a problem and searching for a problem solution using uninformed and heuristically informed search algorithms (search), the representation of knowledge about a problem using different knowledge representation schemes (knowledge representation) and the discovery and generalization of data models collected in the past to apply them to new data in tasks such as classification, predicting, finding data similarities and others (machine learning). The implementation of a two-person game with perfect information, in which a computer plays against a person, is a practical application of the concepts to be taught in the study course about search. The practical work related to the selection, analysis and processing of a dataset ensures the strengthening of knowledge in machine learning. The study course uses a flipped-classroom approach: students independently study the study materials available in the e-study course, devoting lecture time to solving practical tasks working in pairs or small groups. The practical tasks offered in the lectures can be solved both manually and using freely available computer tools intended for a specific purpose (for example, Orange, Segrada, Protégé-Frame, etc.).