📄️ Lesson 1: AI Buzzword Bingo
Basic terms you should familiarize yourself with
📄️ Lesson 2: Top 7 AI Terms
Emerging terms you need to know as AI progresses
📄️ Lesson 3: What is a Large Language Model?
Understanding GPT, LLMs, and how they work.
📄️ Lesson 4: How to Get Better Answers?
Three ways to improve LLM outputs: RAG, Fine-Tuning, and Prompt Engineering.
📄️ Lesson 5: Prompt vs. Context Engineering
Understanding the difference between crafting a prompt and engineering the entire system context.
📄️ Lesson 6: What is a Vector Database?
Bridging the semantic gap with vector embeddings and similarity search.
📄️ Lesson 7: Generative vs. Agentic AI
Understanding the difference between reactive generation and proactive agency.
📄️ Lesson 8: What are AI Agents?
From Monolithic Models to Compound AI Systems and Agents.
📄️ Lesson 9: Agent to Agent Protocol
How AI agents allow collaboration through the A2A standard.
📄️ Lesson 10: Where are the Limits?
Exploring the Data-Wisdom pyramid, past misconceptions, and the future of AI limitations.