To describe the fundamentals concepts, theories, learning models, and techniques in artificial intelligence (AI). Topics include the fundamentals of AI, such as statistics, uncertainty, and Bayes networks; machine learning; logic and planning. The course also addresses the applications of AI, including image processing and computer vision; robotics and robot motion planning; natural language processing and information retrieval. Student can make use of the packages developed on Tensorflow and Scikit-learn to implement some machine learning and AI algorithms. They can learn some hands-on skills, such as building a chat bot, generating some predictive models, and solving searching problems.