Key Generative LLM Models, RAG Architecture, Embedded Models, Agentic AI & MCP Protocol — Hands-On скачать в хорошем качестве

Key Generative LLM Models, RAG Architecture, Embedded Models, Agentic AI & MCP Protocol — Hands-On

Key Generative LLM Models, RAG Architecture, Embedded Models, Agentic AI & MCP Protocol — Hands-On + Case Studies This deep-dive session covers the most important building blocks of modern generative AI systems, combining theory with hands-on demos and real-world case studies. You’ll start by understanding key generative LLMs such as GPT‑4, LLaMA, Claude, and Gemini, including their strengths, limitations, and ideal use cases. We then break down Retrieval-Augmented Generation (RAG) architecture, explaining how vector databases, embeddings, and retrievers enhance LLM accuracy with private and real-time data. You’ll also explore embedded models for on-device and edge AI, agentic AI systems that plan, reason, and act autonomously, and the MCP protocol for standardized multi-agent and tool communication. Core topics include: LLM selection and deployment strategies RAG pipelines with embeddings and vector search Building agentic AI workflows with tools and memory MCP protocol concepts for scalable AI systems Hands-on demos and industry case studies Whether you’re an AI developer, architect, researcher, or startup founder, this session gives you practical skills to design production-ready generative AI systems. Watch till the end to bridge theory with implementation. Subscribe, like, and share for more hands-on AI content. generative llm models, rag architecture tutorial, agentic ai systems, embedded ai models, mcp protocol ai, llm hands on, retrieval augmented generation, ai agents case study, enterprise generative ai #GenerativeAI #LLM #RAG #AgenticAI #EmbeddedAI #MCPProtocol #AIHandsOn #AIArchitecture #CaseStudy #FutureOfAI