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Module 0: Introduction to Universal AI

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Introduction to Universal AI

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.