Don't learn AI Agents without Learning these Fundamentals

🧪AI Agents Labs for Free: https://kode.wiki/3Wh4DZ6 Learn everything about AI agents from scratch in this comprehensive tutorial. No prior knowledge required. We'll take you from zero to building production-ready AI systems with hands-on labs. 🎯 What You'll Learn: • AI Fundamentals - LLMs, tokens, embeddings, and context windows • LangChain - Simplify AI development with pre-built components • Prompt Engineering - Zero-shot, few-shot, and chain-of-thought techniques • Vector Databases - Semantic search with ChromaDB and Pinecone • RAG (Retrieval Augmented Generation) - Build intelligent document search • LangGraph - Create multi-step AI workflows and agents • MCP (Model Context Protocol) - Connect AI to external tools 🔧 Hands-On Labs Include: ✓ Making your first OpenAI API calls ✓ Building semantic search engines ✓ Creating RAG systems for document retrieval ✓ Developing multi-agent workflows ✓ Integrating external tools with MCP Perfect for developers, data scientists, and anyone wanting to understand modern AI development. Follow along with free labs and build a real-world AI assistant that searches 500GB of documents in under 30 seconds. 🚨Start Your AI Journey with KodeKloud: https://kode.wiki/4qsrspX ⏰ TIMESTAMPS: 00:00 - Introduction to AI Agents 00:40 - How LLMs work in real time? 04:56 - Embeddings & Vector Representations 05:56 - How LangChain works? 10:12 - Practice Labs - Your First AI API Call 14:57 - Practice Labs - LangChain 17:57 - Prompt Engineering Techniques 21:21 - Practice Labs - Master Prompt Engineering 24:46 - Vector Databases Deep Dive 31:27 - Practice Labs - Build Semantic Search Engine 35:15 - RAG (Retrieval Augmented Generation) 38:14 - Practice Labs - RAG Implementation 42:14 - LangGraph for AI Workflows 45:51 - Practice Labs - Build Stateful AI Workflow 48:51 - Model Context Protocol (MCP) 51:56 - Practice Labs - Advanced MCP Concepts 55:21 - Conclusion 🔔 Subscribe to KodeKloud for more AI development tools and tutorials! #AiAgents #AI #Aifundamentals #LangChain #MCP #LLMs #RAG #Langgraph #vectordb #promptengineering #VectorDatabases #Tutorial #kodekloud