Week 1: Introduction to Artificial Intelligence (AI)

Day 1: History and evolution of AI

• Early AI concepts and ideas
• Turing Test and AI milestones
• The rise of machine learning and deep learning
• Major breakthroughs and influential researchers in AI

Day 2: AI applications and use cases

• AI in healthcare, finance, and marketing
• AI in natural language processing and computer vision
• AI in robotics and autonomous systems
• AI in entertainment, art, and creativity

Day 3: Types of AI: Narrow AI, General AI, and Superintelligence

• Narrow AI: definition, examples, and limitations
• General AI: goals, challenges, and current research
• Superintelligence: concepts, potential risks, and ethical considerations
• The future of AI: trends and predictions

Day 4: AI technologies and techniques

• Rule-based systems and expert systems
• Machine learning: supervised, unsupervised, and reinforcement learning
• Deep learning: neural networks, convolutional neural networks, and recurrent neural networks
• Other AI techniques: swarm intelligence, evolutionary algorithms, and fuzzy logic