学习用OpenAI、LangChain和React构建生产级AI应用。课程涵盖大模型、RAG、AI智能体、提示词工程及LLMOps部署。适合全栈开发者,助你打通AI全栈开发闭环。

原始标题:Build AI Apps with OpenAI, LangChain & React

Build AI Apps with OpenAI, LangChain & React

该课程是一门面向全栈开发者的实战型 AI 工程化指南,旨在指导学习者利用 OpenAI、LangChain 和 React 技术栈,将 AI 原型转化为高可用、安全的生产级应用。课程内容不仅涵盖大模型基础、提示词工程、流式聊天前端交互和 RAG(检索增强生成)系统构建,更深入探讨了 AI 智能体(Agents)的多步推理与工具调用;在工程落地层面,课程聚焦于 LLMOps 核心痛点,传授防提示词注入、性能与成本优化、模型降级备用、实时监控运维,以及基于 GitHub Actions 的 CI/CD 自动化部署,帮助学员打通从前端交互到云端运维的 AI 全栈开发闭环。

Published 7/2026
Created by SkillBakery Studio
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels | Genre: eLearning | Language: English | Duration: 94 Lectures ( 7h 59m ) | Size: 5.9 GB

Build production-ready AI apps with OpenAI, LangChain, React, RAG, AI Agents, CI/CD, and real-world projects.

What you’ll learn
⚡ Understand how Large Language Models (LLMs) and modern AI applications work.
⚡ Master Prompt Engineering techniques for generating reliable AI responses.
⚡ Integrate OpenAI APIs into real-world applications.
⚡ Build AI-powered applications using LangChain and React.
⚡ Create streaming chat applications with real-time AI responses.
⚡ Develop AI Agents capable of tool calling and multi-step reasoning.
⚡ Build Retrieval-Augmented Generation (RAG) applications.
⚡ Protect AI systems against prompt injection and security risks.
⚡ Optimize AI applications for performance, scalability, and cost.
⚡ Monitor AI quality using logging, analytics, and feedback loops.
⚡ Implement model fallback strategies and prompt A/B testing.
⚡ Build production-ready AI APIs using modern software architecture.
⚡ Automate testing and deployment using GitHub Actions and CI/CD.
⚡ Deploy and maintain AI applications following industry best practices.

Requirements
❗ Basic knowledge of JavaScript is recommended.
❗ Familiarity with React will be helpful but not mandatory.
❗ Basic understanding of APIs and HTTP requests.
❗ A computer running Windows, macOS, or Linux.
❗ Node.js and Visual Studio Code installed.
❗ An OpenAI API key (instructions provided in the course).
❗ A willingness to learn by building real-world AI applications.
❗ No prior experience with LangChain, OpenAI APIs, or AI development is required.

Description
AI Engineering with OpenAI, LangChain & React

Artificial Intelligence is transforming the way modern applications are built. This course is designed to take you beyond simple chatbot examples and teach you how to buildproduction-ready AI applications using today’s most powerful technologies.

Whether you’re a software developer, full-stack engineer, or AI enthusiast, this hands-on course will guide you through every stage of AI application development—from understanding Large Language Models (LLMs) to deploying scalable AI systems in production.

Throughout the course, you’ll build real-world projects while learning how to integrate OpenAI, LangChain, and React to create intelligent applications with streaming responses, AI agents, tool calling, Retrieval-Augmented Generation (RAG), security, monitoring, performance optimization, and deployment best practices.

What you’ll build

✨ AI-powered chat applications

✨ Streaming AI interfaces

✨ AI agents capable of using external tools

✨ Retrieval-Augmented Generation (RAG) applications

✨ Production-ready AI APIs

✨ React-based AI frontends

✨ AI monitoring and analytics dashboards

✨ Secure and scalable AI services

Topics Covered

✨ Prompt Engineering

✨ OpenAI API Integration

✨ LangChain Fundamentals

✨ Streaming AI Responses

✨ React Chat Applications

✨ Function Calling & Tool Calling

✨ AI Agents & ReAct Pattern

✨ Retrieval-Augmented Generation (RAG)

✨ Prompt Injection Protection

✨ AI Security & Guardrails

✨ Token Optimization

✨ Performance & Cost Monitoring

✨ Async & Parallel Processing

✨ AI Observability

✨ Model Fallback Strategies

✨ Prompt A/B Testing

✨ GitHub Actions & CI/CD

✨ Production Deployment Best Practices

By the end of this course, you’ll have the skills and confidence to design, develop, deploy, monitor, and maintain AI-powered applications using modern engineering practices.

If your goal is to become an AI Engineer capable of building production-ready applications—not just prototypes—this course is for you.

Who this course is for
⭐ Software Developers looking to add AI skills to their toolkit.
⭐ Frontend and React Developers who want to build AI-powered user interfaces.
⭐ Backend Developers integrating AI into web applications.
⭐ Full-Stack Developers building intelligent applications.
⭐ Engineers transitioning into AI Engineering roles.
⭐ Students interested in Generative AI and Large Language Models.
⭐ Technical Architects exploring AI application design.
⭐ Anyone who wants to build production-ready AI applications using modern tools and best practices.

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