AI Fundamentals: From ML to Multi-Agent Systems (2026)

Description

Complete guide to modern AI architecture — from Machine Learning basics to building teams of AI agents. ⏱️ Timestamps: 0:00 Introduction 0:35 Machine Learning Basics 1:50 Deep Learning & Neural Networks 3:10 Large Language Models (LLMs) 4:35 RAG — Retrieval Augmented Generation 5:30 AI Agents 6:00 Multi-Agent Systems 6:20 Summary & Next Steps 📚 Topics Covered: • Machine Learning: Supervised, Unsupervised, Reinforcement • Deep Learning: Neural networks, layers, training • LLMs: Transformers, attention, knowledge cutoffs • RAG: Real-time knowledge retrieval • Agents: LLMs with tools and actions • Multi-Agent: Patterns (supervisor, pipeline, debate, swarm) 🔗 Resources: • AutoGen: https://github.com/microsoft/autogen • CrewAI: https://github.com/joaomdmoura/crewai • LangGraph: https://github.com/langchain-ai/langgraph #AIFundamentals #MachineLearning #DeepLearning #LLM #RAG #AIAgents #MultiAgent #TechEducation