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Build Production AI Agents with RAG & MCP · LearnSpace
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Build Production AI Agents with RAG & MCP

Курс от LearnKartS
Средний≈ 12.8 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

Ready to revolutionize AI development? The world of AI is rapidly evolving, and building intelligent, autonomous agents is the next frontier. But how do you go from just understanding AI concepts to creating powerful, production-ready systems? In this course, you’ll not only learn the theory but also gain real-world experience by building AI agents using Gemini and OpenAI. You’ll start by setting up a robust Node.js backend and then integrating Gemini for effortless text generation. Dive deep into creating static RAG systems for advanced Q&A bots and use OpenAI to take your AI’s responses to the next level. Unlike other courses, this Agentic AI course gives you the tools to create scalable, real-world applications like customer service bots and knowledge bases, ensuring your skills are directly applicable in the industry. Whether you're a developer, data scientist, or AI enthusiast, this course will sharpen your AI development skills and prepare you for real-world AI challenges. Don’t just learn about AI—build the future of AI agents. Enroll now and take the first step toward mastering AI development!

Навыки, которые вы освоите

Node.JSTypeScriptRetrieval-Augmented GenerationEmbeddingsModel Context ProtocolOpenAIPrompt EngineeringGeminiWeb ApplicationsAPI DesignOpenAI APIGenerative AI AgentsWeb DevelopmentJavascriptAgentic WorkflowsServer SideGoogle GeminiData ManagementBack-End Web DevelopmentAI Workflows

Программа курса

3 модулей · 76 учебных материалов

01Building the AI Chat Backend and Static RAG System27 материалов

Backend Foundation and Gemini Integration

Course IntroductionВидеоSetting Up the Node.js Backend ProjectВидеоBuilding and Running an Express ServerВидеоUsing Environment Variables, Watch Mode, and NPM ScriptsВидеоIntroduction to Gemini API and Exploring the Documentation

Учитесь у экспертов

LearnKartS

Преподаватель курса

Nikhil Agarwal

Преподаватель курса

Build Production AI Agents with RAG & MCP
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Обучение на Coursera

≈ 12.8 ч

3 модулей

Язык: Английский

Часть программы вашего университета
Видео
Checkpoint QuizЗадание
Proficiency QuizЗадание

Implementing Gemini AI and Building the Chat API

Generating the Gemini API Key and Environment ConfigurationВидеоCreating the Gemini Provider Class and Backend StructureВидеоImplementing Text Generation Using the Gemini SDKВидеоBuilding the Chat API Endpoint and Testing the BackendВидеоCheckpoint QuizЗаданиеProficiency QuizЗадание

Frontend-Backend Connection and Static RAG

Testing NodeJS API in React Chat App - Chat with AIВидеоUnderstanding React Component Structure for the Chat ScreenВидеоRefactoring Chat Components and Improving Code OrganizationВидеоOptimizing UI Design and Finalizing Light/Dark Mode StylingВидеоCheckpoint QuizЗаданиеProficiency QuizЗадание

Building the Knowledge Base and Implementing Static RAG

Setting Up the Knowledge Base and RAG ServiceВидеоPreparing Context and Prompt for Static RAGВидеоIntegrating RAG with Chat Router and Testing the Q&A BotВидеоIntroduction to Embeddings and RAG WorkflowВидеоCheckpoint QuizЗаданиеBuild AI Agents with RAG & MCP: Knowledge Base Setup, Prompt Design & Q&A System IntegrationDIALOGUEProficiency QuizЗаданиеBuilding a RAG-Powered AI Agent with Knowledge Base IntegrationDIALOGUE
02Embeddings and OpenAI-Based Answer Generation19 материалов

Embeddings, Similarity, and Context Selection

Exploring Gemini Embedding API and Task TypesВидеоCreating the Embedding Generation FunctionВидеоInstalling Cosine Similarity and Setting Up RAG UtilitiesВидеоGenerating Query Embeddings and Fetching Knowledge Base DataВидеоCreating FAQ Embedding Vectors from Knowledge BaseВидеоCalculating Cosine Similarity and Selecting Relevant ContextВидеоSetting Up OpenAI API Key and Selecting the ModelВидеоCheckpoint QuizЗаданиеProficiency QuizЗадание

OpenAI Integration and RAG Bot Validation

Creating the OpenAI Provider Class and Installing the SDKВидеоImplementing Response Generation and Embeddings in OpenAIВидеоIntegrating OpenAI with the Chat Router and Testing the LLMВидеоTesting Q&A Bot with OpenAI for AnswersВидеоTesting Error HandlingВидеоInterview Prep: RAG & Similarity QuestionsВидео
03MCP Server Foundation and Tool API Preparation30 материалов

MCP Server Setup and API Structure

Project Initialization & Package InstallationВидеоTypeScript Configuration & tsconfig Setup ВидеоIndex File, Express Setup & Running the ServerВидеоGemini Service Setup & TypeScript IntegrationВидеоRouter Setup & Frontend Testing ВидеоCheckpoint QuizЗаданиеProficiency QuizЗадание

Controller Setup, API Routes, and Tool Preparation

Folder & Controller SetupВидеоData Preparation & Controller Implementation ВидеоRoute Setup & Testing APIsВидеоPreparing a Weather API - Real-World ToolВидеоCheckpoint QuizЗаданиеProficiency QuizЗадание

Building Real-World Tool APIs

Refactoring & Customer Service SetupВидеоCustomer Controller IntegrationВидеоOrder Service DevelopmentВидеоCode Optimization & Order ControllerВидеоGemini Singleton Service & TestingВидеоMCP Architecture & Core ConceptsВидео

Understanding MCP Components and Design Decisions

MCP Implementation, Transport & SessionВидеоUnderstanding MCP Tools: Actions AI Can PerformВидеоMCP Resources Explained: Accessing Read-Only DataВидеоMCP Prompts: Creating Reusable Prompt TemplatesВидеоDecision Framework: When to Use Tool, Resource, or PromptВидеоCheckpoint QuizЗадание
Checkpoint QuizЗадание
Build AI Agents with RAG & MCP: OpenAI Integration, Response Generation & System TestingDIALOGUE
Proficiency QuizЗадание
Integrating OpenAI into an Agentic RAG System and Validating PerformanceDIALOGUE
Checkpoint QuizЗадание
Proficiency QuizЗадание
Building and Optimizing an Agentic AI Backend with MCP and LLM ServicesDIALOGUE
Proficiency QuizЗадание
Course SummaryВидео