零基础掌握Agentic AI、生成式AI及LLM工程，通过Python学习LangChain、LangGraph、RAG与MCP协议，亲手构建AI客服、文档问答等工业级项目，学会自主规划、工具调用与Docker部署，助你独立上线生产力级智能体应用。
原始标题：Agentic AI, Generative AI & LLM Engineering
该课程是一套面向零基础学员的 Agentic AI 与生成式 AI 全栈实战指南，通过 Python 语言深入教授 LangChain、LangGraph、RAG 以及全新的 MCP（模型上下文协议） 等前沿技术。学员将通过亲手构建 AI 客服、文档问答及多智能体协同等丰富的工业级项目，全面掌握自主规划、工具调用、Docker 部署和成本优化等核心工程技能，从而能够独立设计并上线具备生产力级别的智能体应用。
Published 7/2026
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 1h 15m | Size: 912.6 MB
Master Agentic AI, Generative AI, Python, LangChain, LangGraph, RAG, MCP, and Real-World AI Projects
What you’ll learn
Learn to Build Autonomous AI Agents and Production-Ready Generative AI Applications from Scratch
Master Python, LLMs, AI Agents, RAG, Vector Databases, LangChain, and LangGraph Through Real-World Projects
Build Intelligent AI Agents, LLM Applications, RAG Systems, and Full-Stack AI Solutions with Python
Learn Agentic AI Engineering with Python, LangChain, LangGraph, MCP, and Modern AI Frameworks
Requirements
No need to have any experience at all
Description
Take your Artificial Intelligence skills to the next level by mastering Agentic AI and Generative AI through hands-on, real-world projects. This comprehensive course is designed for beginners, software developers, IT professionals, students, and AI enthusiasts who want to build intelligent, autonomous AI applications using Python and the latest AI technologies.
You’ll begin by learning the fundamentals of Python programming, Large Language Models (LLMs), prompt engineering, embeddings, and Generative AI. As your knowledge grows, you’ll explore Agentic AI concepts, including intelligent agents, planning, reasoning, memory, tool calling, workflow automation, and multi-agent collaboration. You’ll understand how modern AI agents think, make decisions, retrieve information, and perform complex tasks autonomously.
Throughout the course, you’ll gain practical experience with industry-leading tools and frameworks, including OpenAI APIs, LangChain, LangGraph, CrewAI, AutoGen, Hugging Face, Ollama, Retrieval-Augmented Generation (RAG), Model Context Protocol (MCP), vector databases, FastAPI, Streamlit, Docker, Git, and cloud deployment. You’ll learn how to integrate AI models with external APIs, databases, enterprise systems, and modern web applications to build scalable, production-ready AI solutions.
This course focuses on project-based learning. You’ll build a wide range of real-world applications, including AI chatbots, intelligent virtual assistants, document question-answering systems, AI-powered search applications, coding assistants, workflow automation tools, customer support bots, research assistants, content generation platforms, multi-agent systems, and end-to-end AI business applications. Each project is carefully designed to strengthen your practical development skills and help you build a professional portfolio.
You’ll also learn industry best practices for AI engineering, including prompt optimization, structured outputs, model evaluation, AI security, testing, deployment, monitoring, performance optimization, and cost-efficient AI application development. These skills will prepare you to create reliable, secure, and scalable AI systems for real-world use.
By the end of this course, you’ll have the confidence and expertise to design, develop, deploy, and maintain intelligent Agentic AI and Generative AI applications. Whether you’re looking to start a career in AI, enhance your software development skills, build innovative AI products, automate business workflows, or create a strong portfolio of AI projects, this course provides everything you need to become a successful AI developer.
Who this course is for
It is for anyone who wants to master Agentic AI and Generative AI from basics to Advanced
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