By Stanford University

Part I: Fundamentals of AI

• Overview of AI
• Statistics, Uncertainty, and Bayes networks
• Machine Learning
• Logic and Planning
• Markov Decision Processes and Reinforcement Learning
• Hidden Markov Models and Filters
• Adversarial and Advanced Planning

Part II: Applications of AI

• Image Processing and Computer Vision
• Robotics and robot motion planning - Natural Language Processing and Information Retrieval

Here’s the free course- (link)