Agentic AI Bootcamp: 40 Hours of Live Code Along

5.0 (3)

Nitin Monga

AI Engineer & Founder

8 Weeks Build Agentic AI Application you can show Employer, Clients or Investors

5 cohorts · 5.0★ rating · alumni at Meta, Oracle, NVIDIA, JP Morgan Chase, ICICI Bank, National Bank of Kuwait, Bluemarlin, LiveRamp, Ogilvy, Teradata

You've watched the tutorials. You still can't ship an agent.

This bootcamp fixes that. Every single session is live. Every topic is code-along. You open your editor, I open mine, & we build multi-agent systems with LangChain, LangGraph & MCP line by line — 40 Hours of live sessions, the most live instruction of any AI bootcamp on Maven.

And it ends with something no tutorial gives you: a production agentic AI app running on AWS under your own custom domain. Not a notebook. Not a localhost demo. A live URL you can put in front of employers, clients, and investors.

You graduate with:

A deployed multi-agent AI application — live on the cloud, on YOUR domain
Multi-agent orchestration: LangChain + LangGraph + MCP + Memory
Build complete RAG/Agentic RAG Application with Vector Databases like CromaDB & Pinecone

Other Cohort - I have received 10+ five-star reviews. You can check the reviews and feedback here: Maven reviews

What you’ll learn

Master LangChain, LangGraph, Agentic RAG, MCP - create the intelligent, autonomous AI workflows & AI Agents like - https://www.aitripy.com

Architect an autonomous Multi AI Agents that collaborate & interacts with tools, APIs, and users end-to-end.
Containerize with Docker and deploy on AWS ECS behind your own custom domain
Leave with a live URL — the portfolio piece employers and clients actually click

Build stateful agent workflows with LangGraph: routing, cycles, human-in-the-loop
Design multi-agent patterns — planner/executor, supervisor, agent-to-agent handoffs
Connect agents to tools and data through MCP servers you build yourself

Ingest data with loaders, splitters, and vector DBs ( ChromaDB, Pinecone/ Qdrant)
Go beyond static RAG: retrieval planning, reranking, and context engineering
Evaluate retrieval quality so you can prove your system works — not just hope

Serve your agent with FastAPI and ship a working UI with Streamlit
Use Claude Code and Cursor as pair programmers to accelerate every build
Wire CI/CD so deployments are repeatable, not heroic

Define a real-world use case (founder / entrepreneur / solopreneur angle), design the MVP (minimum viable product) for that case.
Build the MVP during the course and deploy it with a custom domain or production target.
Present your agent project as a capstone/demo day, ready for LinkedIn, portfolio, clients or investors.

Understand high-level architecture of agent-based systems, model context protocol (MCP), and multi-agent ecosystems.
Gain confidence to lead AI initiatives, pitch agent-based solutions, and consult or work as an agent-builder.
Walk into AI engineering interviews able to explain and defend every decision in your system

Learn directly from Nitin

Nitin Monga

Contact

AI Engineer & Founder - Data Science/Machine Learning/ Artificial Intelligence

See all products from Nitin

Who this course is for

Developers & Professionals Pivoting into AI
Build & deploy AI Agents; fast-track careers into the most in-demand and high paying tech domain
Entrepreneurs & Founders
Aiming to launch AI-powered SaaS products, automate workflows, or integrate intelligent agents into their business
Product Managers
Looking to lead AI-driven product development, understand agent architecture & collaborate effectively with technical team

What's included

Live sessions

Learn directly from Nitin Monga in a real-time, interactive format.

40+ Hours of Live - Code Along Sessions

40+ hours of live, code-along sessions - the most live AI Bootcamp on Maven. You code in every class. No passive watching. You build real agentic systems alongside me in real time. You write every line, debug every error, and ship working agents. By the end, you won't just understand agents; you'll have built them.

Deploy Your Own Agentic AI App on a Custom Domain

Build and deploy a production-ready Agentic AI application using LangChain and LangGraph—hosted on AWS under your own custom domain (just like www.aitripy.com). By the end of this course, you won’t just learn—you’ll launch. Showcase your AI expertise with a live, interactive application that employers, clients, and peers can access anytime.

Certificate of completion

Share your new skills with your employer or on LinkedIn.

Exclusive Community Access

Collaborate, learn, and grow with a vibrant network of AI builders, innovators, and professionals. Stay engaged through discussions, project

Extensive Learning Resources

Get lifetime access to 100+ pages of curated reading material, architecture diagrams, implementation guides, and exclusive eBooks.

The Agent Builder's Library

100+ pages of guides, 20+ architecture diagrams, every repo we build in class, plus my personal templates and decks. Lifetime access, updated each cohort.

Miss a Class - All Classes are Recorded

Travel, an office deadline, something at home — it happens. Every session is recorded and available the same day, not weeks later. And if the recording leaves you with questions, we get on a call offline and clear them one-to-one.

Lifetime Access & Switch to Future Cohort

Go back to the course content and recordings whenever you need to. Plans changed and you can’t attend the classes? No worries! Just let us know, and we’ll move you to the next cohort.

Don't just learn. Build the thing you actually need & aspire

This is the part most people miss. Come in with the app you want running at work — the internal assistant, the document pipeline, the research agent your team keeps asking for. We build the 5 portfolio projects together, & alongside them you build yours.

Maven Guarantee

Your purchase is backed by the Maven Guarantee.

Course syllabus

Week 1

Sep 20

Sep

Agentic AI Bootcamp - Orientation and Environment Readiness

Sun 9/2012:30 AM—2:30 AM (UTC)

Week 2

Sep 21—Sep 27

Sep

LangChain - Models - Frontier Model, Open Source Models, HuggingFace & Ollama Models

Thu 9/241:30 AM—2:30 AM (UTC)

Sep

LangChain - Models & Prompt - Open Source Models, HuggingFace & Ollama Models. Introduction to Prompts

Sat 9/2612:30 AM—2:30 AM (UTC)

Sep

LangChain - Structured Output & Parsers - TypedDict, Pydantic and Json Schema

Sun 9/2712:30 AM—2:30 AM (UTC)

Schedule

Live sessions

4-5 hrs / week

Sun, Sep 20
12:30 AM—2:30 AM (UTC)
Thu, Sep 24
1:30 AM—2:30 AM (UTC)
Sat, Sep 26
12:30 AM—2:30 AM (UTC)

Projects

1-2 hrs / week

Async content

1-2 hrs / week

Projects you will build

First, you master retrieval

01 · YouTube RAG Chatbot — question any video's transcript

02 · LangGraph Conversational RAG — working memory

03 · LangGraph SQL Agent — plain English → SQL, self-correcting queries

04 · Multi-Agent Research Assistant — a supervisor delegates to specialists and assembles a sourced brief

05 · Agentic RAG, Hybrid Retrieval — a router picks vector DB or SQL, then synthesizes both

06 · Social Media Multi-Agent System — research → write → review pipeline with a human-approval gate

07 · Your Own MCP Server — expose custom tools any agent (including Claude) can use

Every repo is yours forever. If it's in your portfolio, you wrote it.

Capstone Project

A production multi-agent system, live on your own domain. Everything converges into one build — a full multi-agent application where specialized agents research, reason, retrieve, and collaborate to complete real tasks end to end. You'll architect it with LangGraph orchestration, MCP tools, a FastAPI backend, a Streamlit front-end, Docker, and AWS. Then we deploy it together to your own custom domain and you present it at Demo Day.

Employers don't click GitHub links. They click yours AI App deployed