| Days | Content Title | Key Concepts Covered |
| Days 1-7 | AI Fundamentals | Definition of AI, Machine Learning (ML) vs. Deep Learning (DL), Types of ML: Supervised, Unsupervised, Reinforcement Learning. |
| Days 8-14 | The ML Workflow | Data Collection, Feature Engineering (Conceptual), Model Training (Conceptual), Evaluation Metrics. |
| Days 15-21 | Generative AI Introduction | What is Generative AI? Large Language Models (LLMs), Key architectures (Transformers – Conceptual). |
| Days 22-30 | Prompt Engineering & Tools | Prompt Engineering techniques (Zero-shot, Few-shot), Practical use of tools like ChatGPT/Gemini, AI in the workplace, Final Project: A portfolio of optimized prompts for various tasks. |
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