This course covers some advanced topics in machine learning and artificial intelligence for solving analytics problems and building business applications. Topics include but are not limited to: reinforcement learning and recent advances on natural language processing. Students are introduced to the basic concepts of reinforcement learning such as Markov decision process, bandits, and regret minimization, and are trained to build simple and practical reinforcement learning systems. The course also discusses some recent progress in natural language processing / understanding, such as representation learning, sequential models, and transformer models, as well as their business applications.