LearnKartS

Agentic AI Engineering: RAG, MCP & MERN 专项课程

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LearnKartS

Agentic AI Engineering: RAG, MCP & MERN 专项课程

Master Agentic AI Engineering.

Go beyond chatbots, build intelligent AI agents with RAG, MCP & MERN

LearnKartS
Nikhil Agarwal

位教师:LearnKartS

包含在 Coursera Plus

深入学习学科知识
初级 等级

推荐体验

4 周 完成
在 10 小时 一周
灵活的计划
自行安排学习进度
深入学习学科知识
初级 等级

推荐体验

4 周 完成
在 10 小时 一周
灵活的计划
自行安排学习进度

您将学到什么

  • Master the foundations of Agentic AI, RAG, and MCP, and how they transform AI systems into adaptive, autonomous agents for real-world applications. 

  • Gain hands-on experience building scalable AI systems with the MERN stack, integrating React, Node.js, & MongoDB for dynamic, real-world solutions. 

  • Dive into advanced AI concepts like embeddings and context retrieval, combining OpenAI and Gemini models to create responsive, personalized agents. 

  • Build an AI agent from the ground up, gaining practical skills in frontend, backend, and tool integration to prepare for high-demand AI roles.

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授课语言:英语(English)
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专业化 - 4门课程系列

Agentic AI Foundations with MERN, RAG & MCP

Agentic AI Foundations with MERN, RAG & MCP

第 1 门课程, 小时

您将学到什么

  • Dive into Agentic AI, RAG, and MCP to create next-gen, intelligent systems with real-world applications.

  • Build powerful MERN stack projects, integrating Node.js, React, and Gemini AI for dynamic chat solutions.

  • Master modern frontend techniques with React, Vite, and TypeScript, crafting a fully responsive, polished UI.

  • Gain hands-on experience building andoptimizingscalable AI-powered chat apps, ready for real-world deployment.

Build Production AI Agents with RAG & MCP

Build Production AI Agents with RAG & MCP

第 2 门课程, 小时

您将学到什么

  • Master building AI-powered chat systems with Node.js and Gemini API for seamless text generation and dynamic responses.

  • Implement static RAG systems andleverageknowledge bases to create advanced, responsive AI-driven Q&A bots.

  • Integrate OpenAI with RAG for intelligent response generation, improving accuracy and enhancing user experience.

  • Build real-world tool APIs using MCP, including customer service and weather APIs, to elevate AI system performance.

Advanced MCP & Tool Calling for AI Agents

Advanced MCP & Tool Calling for AI Agents

第 3 门课程, 小时

您将学到什么

  • Understand MCP architecture, tool calling concepts, and practical setup for Gemini and OpenAI integration.

  • Master tool registration, function calling, and response generation in Gemini and OpenAI environments.

  • Learn to build and configure the MCP server, transport layer, and API routes for seamless client-server communication.

  • Gainexpertisein integrating OpenAI with MCP, setting up Angular for AI-assisted development, and creating agent-driven systems.

Agentic AI Systems with Vector DBs & RAG

Agentic AI Systems with Vector DBs & RAG

第 4 门课程, 小时

您将学到什么

  • Dive intoRAG (Retrieval-Augmented Generation)and understand how to build smarter, context-aware AI systems with real-time data retrieval.

  • MasterAgentic AIconcepts, enabling systems to evolve, learn, and adapt autonomously in real-time based on dynamic data.

  • Learn how to implementpgVectorandChromaDB, integrating vector databases for efficient AI memory and fast data retrieval.

  • Gain hands-on experience building scalable, adaptive AI solutions that can continuously improve with every interaction and data input.

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