What you'll learn

• Explain what AI is and how AI agents operate, including perception, reasoning, action, and the role of data.
• Distinguish between symbolic (rule‑based) AI and modern machine learning, and understand how each approach solves problems.
• Describe how machine learning models are trained, including training/validation/test splits, inference, and generalization.
• Understand how generative AI systems create content, and what makes them different from earlier AI models.
• Assess real‑world AI applications across sectors, including health care, education, and agriculture, and identify the constraints that shape their performance.
• Recognize the societal, ethical, and practical challenges of AI, including bias, explainability, misconceptions, and responsible deployment.