An AI course outline typically covers foundational concepts, machine learning techniques, and real-world applications. It begins with an introduction to AI, covering history, types, and ethical considerations. The course then explores machine learning (supervised, unsupervised, and reinforcement learning), deep learning (neural networks, CNNs, RNNs), and natural language processing (NLP). It includes hands-on projects using tools like Python, TensorFlow, or PyTorch. Advanced topics may include computer vision, robotics, and AI ethics. The course concludes with AI deployment, industry trends, and a capstone project to reinforce learning.