AI Academy: Prompt & RAG
Learn prompt engineering and production RAG from an enterprise AI engineer.
About
Learn prompt engineering and RAG from an engineer who builds these systems for Fortune 500 companies. AI Academy takes you from writing your first prompt to deploying production RAG (Retrieval Augmented Generation) systems — the architecture behind enterprise AI assistants, knowledge bases, and intelligent search. WHAT YOU'LL LEARN Prompt Engineering Fundamentals - Prompt structure and optimization - Chain-of-thought and tree-of-thoughts techniques - Few-shot learning and context management - Task-specific prompting (code, writing, analysis) Enterprise RAG Systems - Document chunking and preprocessing - Embedding models and vector databases - Retrieval strategies and re-ranking - Production deployment and scaling PRACTICE WITH REAL AI Get instant feedback on your prompts from GPT-5 and Claude 4.5. See exactly how your prompts perform and how to improve them. HOW IT WORKS - 50+ structured lessons from basics to advanced - Daily challenges to build consistent skills - Flashcards for key concept retention - Progress tracking across all modules WHO THIS IS FOR - Developers adding AI to their products - Product managers working with AI teams - Anyone who wants to use AI more effectively at work - Engineers transitioning into AI/ML roles FREE TO START Complete the first 3 prompt engineering topics and preview RAG fundamentals free. Upgrade to unlock the full curriculum, all RAG modules, and AI-powered feedback. --- Created by an engineer with 25 years in ICT and enterprise LLM deployments.
How to Use
- Open AI Academy and start with the fundamentals of prompt engineering. 2. Practice writing prompts and progress through lessons toward more advanced topics. 3. Learn how Retrieval Augmented Generation (RAG) works, the architecture behind enterprise AI assistants and knowledge bases. 4. Follow the guidance toward deploying production RAG systems. 5. Apply the concepts to your own AI projects as you advance.
✓ Pros
- •Covers prompt engineering and RAG end to end
- •Taught by an experienced industry engineer
- •Focused on production-grade AI systems
✗ Cons
- •Niche, technical audience
- •Assumes some engineering background
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