This course introduces Artificial Intelligence (AI) and is designed for students from different backgrounds but with affinity to science, technology, and computing. The field of AI has progressed significantly in recent years with impressive advances particularly in machine learning for solving complex problems by processing and classifying data at speed. AI encompasses a range of techniques that aim to solve problems that would normally require some degree of human intelligence. Machine learning is perhaps the AI technique that has received most attention in recent years due to its success in solving complex games, pattern recognition, and content generation. Other AI techniques like inference logic, intelligence agents, Bayesian networks, heuristic search and evolutionary computation are also important to solve complex problems in many applications. This course gives an insight into AI as the discipline that studies intelligent algorithms, how they work and how they are constructed and programmed. The course includes practical exercises for students to experiment with some of the AI techniques studied. An understanding of the fundamentals of computer algorithms and some experience in computer programming in any language is required. It is also essential that students have access to their own computer during the course.

Biopsychology is an interdisciplinary science which investigates biological mechanisms underlying human and animal behavior. Through this course, students should be able to • Gain basic knowledge of anatomy and physiology of the central nervous system. • Learn how various brain functions and dysfunctions including sensation and perception, learning and memory, emotion and motivation, language and cognition as well as neurological and psychiatric disorders are described by underlying biological, chemical, and computational principles. • Understand the basic methodology used in biopsychology research. • Read and criticize a research article published in scientific journal.

This course introduces the world of computer science and is designed for students from different backgrounds as no prior knowledge of computing is assumed. This course gives an insight into computer science as the discipline that studies computers and computer systems, how they work and how they are constructed and programmed. This course will enable students to gain an understanding of the following: the way computers store and process information, the organization of hardware, the way computer networks and computing paradigms (including an overview of artificial intelligence) work, the construction of computer programs with emphasis on algorithms and data structures to solve a variety of real-world problems. The course also gives a gentle introduction to computer programming using the Java programming language. Students will learn to understand, to modify and to write Java computer programs. Students will also work on a group project to develop a computer program in Java for a set of given tasks. Since part of this course involves learning and practicing computer programming, it is essential that students have access to their own computer during the course.

This is an introductory course in game theory, a branch of applied mathematics. Game theory is a general theory of behavior and, as such, it is a part of social science. Its impact of the last three decades has been extraordinary. This class is a reasonably comprehensive introduction to modern game theory. We will cover theory of preferences, expected utility theory, and a variety of solutions concepts including iterated dominance, Nash equilibria, subgame perfect equilibria, evolutionary equilibria and others.