Level Up LLM App Development with LangChain & OpenAI

这是一门关于使用LangChain与OpenAI提升LLM应用开发能力的实践课程。课程将系统教授如何利用LangChain框架与OpenAI API构建大语言模型应用，涵盖提示工程、链式工作流、检索增强生成（RAG）、向量搜索与智能体开发等核心内容。学员将学习创建多工具智能体、连接数据库、构建语义搜索管道，并最终通过Streamlit、LangServe等工具将完整的AI应用部署至云端。课程适合从初学者到希望将LLM集成到实际项目的开发者，无需深厚Python基础即可跟随实践，旨在提供构建、优化与部署新一代智能应用程序的完整技能。

MP4格式 | 视频：h264编码，分辨率1280×720 | 音频：AAC编码，采样率44.1kHz，双声道 |
语言：英语 | 时长：3小时51分钟 | 文件大小：1.95 GB

Build LLM apps with LangChain, OpenAI, RAG, agents, vector search, and deploy full AI applications to the cloud.

What you’ll learn
Build LLM-powered applications using LangChain and OpenAI APIs.
Implement Retrieval-Augmented Generation (RAG) to enhance model outputs.
Create intelligent agents with tools, functions, and multi-retriever workflows.
Deploy LLM apps to the cloud using LangServe, Streamlit, and Replit.

Requirements
Basic Python knowledge is helpful but not required. Beginners can follow along easily.

Description
Large Language Models (LLMs) are transforming how modern applications are built, and this course shows you exactly how to leverage their full power. Whether you are a beginner exploring AI development or a developer looking to integrate LLMs into real-world projects, this course provides a complete, hands-on roadmap.You will start by learning how to interface with LLMs efficiently using LangChain and OpenAI APIs. Step-by-step, you’ll discover how to structure prompts, build chains, and create intelligent workflows that combine models, tools, and outputs. From there, you will explore Retrieval-Augmented Generation (RAG) by building vector stores, generating embeddings, and enabling your applications to access relevant documents and provide more accurate responses.The course also guides you through building multi-retriever agents capable of analyzing queries, pulling data from multiple sources, and performing complex reasoning tasks. You’ll develop interactive chat applications, connect databases such as MongoDB, and implement semantic search pipelines.Finally, you will learn how to deploy your AI applications using Streamlit, LangServe, Replit, and cloud services. By the end of this course, you will have the skills to build, optimize, and deploy powerful AI-driven applications that deliver real value.Whether you’re aiming to enhance your professional skillset or launch new AI projects, this course gives you the practical foundation needed to build the next generation of intelligent applications.