LangChain & LangGraph: Building Agentic AI, RAG & Chatbots
★ 4.4 rated · $10.99
Build & Deploy 10 Production AI Agents with LangChain v1, LangGraph, MCP, Gemini 3, FastAPI, Streamlit & AWS EC2
$9.99 with coupon (list $149.99 — save $140.00, 93% off)
Coupon Verified: October 16, 2026 · click Claim Coupon to apply the discount code
Our verdict: worth it — as long as the Development skills on the syllabus match what you actually want to learn. The regular price for Agentic AI Projects: FastAPI, MCP, AWS Deploy & Gemini 3 on Udemy is $149.99. With the coupon code on this page, that falls to $9.99 — a saving of $140.00, or 93% off the standard rate Spread across 26h 47m of on-demand video, that works out to roughly $0.37 per hour of content — cheaper than a single chapter of most printed Development textbooks.
A cheap price means nothing if the material is thin — here the syllabus is organized around usable outcomes. Laxmi Kant | KGP Talkie walks you through build real AI agents using LangChain and Google Gemini that can reason, use tools, and complete tasks autonomously, design agent architectures using ReAct patterns, tool calling, and structured decision making, and implement short-term and long-term memory in AI agents using databases and embeddings for personalized experiences — skills meant to be used, not just watched. It has already been taken by 1,972 students and holds a 4.4-star average from verified reviews, which suggests the content holds up once learners actually apply it.
Check the prerequisites before you commit: Basic knowledge of Python, including functions, variables, and working with libraries; Familiarity with running Python code in notebooks or a code editor like VS Code. Best suited to learners who already have footing in Development. Plan for roughly 26h 47m of on-demand video at your own pace. Lessons are delivered in English.
Practical skills and outcomes you'll gain from Agentic AI Projects: FastAPI, MCP, AWS Deploy & Gemini 3 — taken from the official Udemy syllabus for Development learners.
Build real AI agents using LangChain and Google Gemini that can reason, use tools, and complete tasks autonomously.
Design agent architectures using ReAct patterns, tool calling, and structured decision making.
Implement short-term and long-term memory in AI agents using databases and embeddings for personalized experiences.
Create and manage agent tools for web search, weather, finance, document analysis, and external APIs.
Apply prompt engineering techniques to control agent behavior, improve output quality, and guide tool usage.
Add safety layers such as guardrails, human-in-the-loop approval, and middleware controls to prevent errors and misuse.
Stream real-time responses and generate structured outputs from AI agents in production-style applications.
Secure AI agents with sandboxed code execution to prevent file deletion, credential leaks, and system risks.
What you need before enrolling in Agentic AI Projects: FastAPI, MCP, AWS Deploy & Gemini 3 — prerequisites as listed by the instructor on Udemy.
Basic knowledge of Python, including functions, variables, and working with libraries
Familiarity with running Python code in notebooks or a code editor like VS Code
A computer with internet access to use cloud APIs and developer tools
Willingness to learn and experiment with AI and new technologies
No prior LangChain, LangGraph, or MCP experience required — everything is taught from the ground up
The full official description of Agentic AI Projects: FastAPI, MCP, AWS Deploy & Gemini 3 — curriculum, teaching approach, and everything included with this Udemy coupon.
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Common queries about this coupon, pricing, and enrollment. Answers reflect our last check on October 16, 2026.
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