Build AI Apps with OpenAI, LangChain & ReactPublished 7/2026
Created by SkillBakery Studio
MP4 |
Video: h264, 1920x1080 |
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.⚡ 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.
DescriptionAI 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 build
production-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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