The dream of creating artificial devices that reach or outperform human intelligence is many centuries old. In this course I will present an elegant parameter-free theory of an optimal reinforcement learning agent embedded in an arbitrary unknown environment that possesses essentially all aspects of rational intelligence. The theory reduces all conceptual AI problems to pure computational questions.