• AI Masterclass|AI Fundamentals to Vibe Engineering · 19 Oct – 13 Nov · Limited Seats

LIVE MASTERCLASS · 19 OCT – 13 NOV

Stop Watching AI.
Start Building It.

Build, ship and secure real AI agents with Claude Code, RAG, MCP and LangGraph, live, with mentors beside you while you build. Mon–Fri live classes and guided build labs, 90 minutes a day, plus a post-program support week.

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Learners Trained

Companies Trained

Live Days per Cohort

Projects You Ship

REAL AI TRAINING EXPERIENCE

Learn AI Through Real-World Training

Experience practical AI learning through hands-on sessions, live demonstrations, and real-world implementation.

Live AI training session with participants

WHAT OUR LEARNERS SAY

Built for Learners Who Want to Build With AI

From learning the fundamentals to building real AI applications, our learners use the program to turn AI concepts into practical skills.

Arjun Mehta

Software Engineer

I had been learning AI through scattered videos and tutorials, but I never knew how everything connected. This program gave me a clear path from Python and machine learning to LLMs, RAG, agents, and deployment.

Priya Nair

Python Developer

What I liked most was the practical approach. We didn't just learn what an LLM or RAG system is, we actually built them. The hands-on projects made the concepts much easier to understand.

Rahul Sharma

Technology Professional

I was interested in AI but honestly didn't know where to start. The course starts with the fundamentals and gradually moves into much more advanced topics. Having live guidance made the learning much easier.

Karthik Raj

Full-Stack Developer

The biggest value for me was learning how to turn AI concepts into working applications. Building an AI-powered project, connecting APIs, working with RAG, and deploying the application gave me a much better understanding of real AI development.

Sneha Kapoor

Business Operations Manager

I didn't join the program just to understand AI terminology. I wanted to understand how AI could actually automate work. The workflow automation and AI agent projects helped me see how these technologies can solve real business problems.

Arjun Mehta

Software Engineer

I had been learning AI through scattered videos and tutorials, but I never knew how everything connected. This program gave me a clear path from Python and machine learning to LLMs, RAG, agents, and deployment.

Priya Nair

Python Developer

What I liked most was the practical approach. We didn't just learn what an LLM or RAG system is, we actually built them. The hands-on projects made the concepts much easier to understand.

Rahul Sharma

Technology Professional

I was interested in AI but honestly didn't know where to start. The course starts with the fundamentals and gradually moves into much more advanced topics. Having live guidance made the learning much easier.

Karthik Raj

Full-Stack Developer

The biggest value for me was learning how to turn AI concepts into working applications. Building an AI-powered project, connecting APIs, working with RAG, and deploying the application gave me a much better understanding of real AI development.

Sneha Kapoor

Business Operations Manager

I didn't join the program just to understand AI terminology. I wanted to understand how AI could actually automate work. The workflow automation and AI agent projects helped me see how these technologies can solve real business problems.

Vikram Menon

Technology Career Transitioner

Before joining, I was overwhelmed by the number of AI tools, frameworks, and concepts available. This program gave me a structured learning path and projects I could actually talk about.

Aditya Kumar

AI Developer

The project-based format was exactly what I was looking for. From building an LLM application and a RAG system to working with automation and deployment, every module pushed me to actually create something.

Neha Verma

Founder & Entrepreneur

As a founder, I wanted enough technical understanding to evaluate AI ideas and build useful prototypes. The course helped me understand where LLMs, agents, automation, and RAG fit into real products.

Rohan Iyer

AI & Software Engineer

The capstone was one of the strongest parts of the program for me. Instead of finishing with notes and a certificate alone, I had a complete AI project that I could demonstrate and discuss.

Arjun Mehta

Software Engineer

I had been learning AI through scattered videos and tutorials, but I never knew how everything connected. This program gave me a clear path from Python and machine learning to LLMs, RAG, agents, and deployment.

Vikram Menon

Technology Career Transitioner

Before joining, I was overwhelmed by the number of AI tools, frameworks, and concepts available. This program gave me a structured learning path and projects I could actually talk about.

Aditya Kumar

AI Developer

The project-based format was exactly what I was looking for. From building an LLM application and a RAG system to working with automation and deployment, every module pushed me to actually create something.

Neha Verma

Founder & Entrepreneur

As a founder, I wanted enough technical understanding to evaluate AI ideas and build useful prototypes. The course helped me understand where LLMs, agents, automation, and RAG fit into real products.

Rohan Iyer

AI & Software Engineer

The capstone was one of the strongest parts of the program for me. Instead of finishing with notes and a certificate alone, I had a complete AI project that I could demonstrate and discuss.

Arjun Mehta

Software Engineer

I had been learning AI through scattered videos and tutorials, but I never knew how everything connected. This program gave me a clear path from Python and machine learning to LLMs, RAG, agents, and deployment.

Learn AI by building. Build skills you can demonstrate.

What You Will Build

Four portfolio projects. You ship something real every single week.

WEEK 1 · VIBE CODING

AI App v1

A vibe-coded LLM app built with Claude Code: spec it, let AI build it, review it, and ship it with cost controls.

Claude CodeCursorOpenAI · Anthropic · GeminiStreamlit

WEEK 2 · RAG

Ask-My-Docs

A RAG assistant grounded in your own documents that cites its sources, with a golden test set measuring answer quality.

ChromapgvectorEmbeddingsRerankersOllama

WEEK 3 · AGENTIC AI

Ops Agent

A tool-using agent built on your own MCP server, with memory, approvals, and the right tool for every task.

LangChainLangGraphMCPA2An8n

WEEK 4 · CAPSTONE

Your Capstone

A deployed, evaluated AI agent on a real-world track: Legal, Healthcare, BFSI, Sales & Ops, or your own idea.

EvalsGuardrailsMCPCloud DeployLive URL

WHAT YOU'LL LEARN

From AI Fundamentals to Vibe Engineering

Six modules that build on each other, one week at a time, with vibe engineering using Claude Code and Cursor woven into every week.

MODULE 01 · WEEK 1

GenAI Building Blocks

How LLMs work: tokens & context windows
Prompting, function calling & structured output
The modern AI stack: providers & platforms
Latency, cost & reliability basics
Vibe coding with Claude Code & Cursor

PRACTICE PROJECT

Ship AI App v1: a vibe-coded LLM app with cost controls, deployed and demoed to the cohort.

MODULE 02 · WEEK 2

Context Engineering & RAG

Context engineering beyond prompts
Embeddings, chunking & vector databases
Retrieval strategies that stay grounded
Advanced RAG: hybrid search & reranking

PRACTICE PROJECT

Ground AI in a real document set (policies, contracts or manuals) and answer with source citations.

MODULE 03 · WEEK 2

Fine-tuning & Local Models

When fine-tuning pays off, and when not
Efficient tuning with LoRA & QLoRA
Running open models locally with Ollama
Cloud vs local: quality & cost trade-offs

PRACTICE PROJECT

Ship Ask-My-Docs: a RAG assistant with a golden test set and measured answer quality.

MODULE 04 · WEEK 3

The Agentic Leap

What makes a system truly agentic
Agentic architecture patterns, tools & memory
MCP and Agent-to-Agent (A2A)
LangChain & LangGraph deep dive

PRACTICE PROJECT

Ship Ops Agent: a LangGraph agent using your own MCP server, with memory and an approval step.

MODULE 05 · WEEK 4

Evals, Observability & Monitoring

Golden datasets & failure analysis
LLM-as-a-judge evaluation
Monitoring platforms for production
Eval loops that catch hallucinations

PRACTICE PROJECT

Capstone: add a golden eval set, tracing and monitoring, with a mentor review of your architecture.

MODULE 06 · WEEK 4

AI Security & Safety

The AI threat surface & attack patterns
Prompt injection & hallucinations
PII protection & secure data handling
Guardrails, red teaming & governance

PRACTICE PROJECT

Demo Day: present your secured, deployed capstone to the LuMay panel and earn your certificate.

WEEK 5 · POST-PROGRAM

Launch & Get Seen

Support hours: open build lab with mentors
Doubt clearing across every module
LinkedIn branding & capstone launch post
Final portfolio review: GitHub, README & demo

PRACTICE PROJECT

Leave with a finished portfolio, and a LinkedIn profile that shows it.

IS THIS FOR YOU?

Who Should Attend?

Two lanes, one cohort: a Builder lane for people who want to code AI systems in Python, and an Applied lane for leaders building with no-code tools like n8n.

Developers & Engineers

Builder lane: code real AI systems in Python, including agents, RAG, and your own MCP servers.

Data Professionals

Builder lane: turn data skills into production AI apps with evals and cloud deployment.

Career Switchers

Builder lane: build a deployed portfolio that proves you can ship AI.

Managers & Leaders

Applied lane: build with no-code tools like n8n and lead AI work with confidence.

Founders & Startups

Applied lane: prototype AI products fast and know what production really takes.

Consultants & Coaches

Applied lane: advise on AI adoption backed by hands-on, shipped experience.

Developers & Engineers

Builder lane: code real AI systems in Python, including agents, RAG, and your own MCP servers.

Data Professionals

Builder lane: turn data skills into production AI apps with evals and cloud deployment.

Career Switchers

Builder lane: build a deployed portfolio that proves you can ship AI.

Managers & Leaders

Applied lane: build with no-code tools like n8n and lead AI work with confidence.

Founders & Startups

Applied lane: prototype AI products fast and know what production really takes.

Consultants & Coaches

Applied lane: advise on AI adoption backed by hands-on, shipped experience.

WHY THIS PROGRAM

Most AI Courses Teach You About AI. This One Has You Ship It.

You build on 12 of 20 live days: short, sharp classes followed by guided build labs where mentors unblock you in real time.

GenAI Foundations

How LLMs really work: tokens, context windows, function calling and structured output, plus the modern AI stack teams use today.

RAG & Context

Anchor your AI in truth with embeddings, vector databases and retrieval strategies, and learn when fine-tuning actually pays off.

Agentic AI

Turn an LLM into an agent that reasons, uses tools and takes action, with MCP, A2A, LangChain and LangGraph.

Evals & Safety

Make it production-grade with golden datasets, LLM-as-a-judge, monitoring, guardrails and red teaming: the skills that separate a toy from a product.

Vibe Engineering

In every week: spec it, let Claude Code build it, review it, ship it, and learn to check what AI pair programmers write.

LEARN FROM PRACTITIONERS

Learn from Reshma Sriraman

Live Mentor

Lead Mentor

Reshma Sriraman

Director, AI Product Enablement, Enterprise Training & AI Adoption at LuMay AI. Reshma helps learners move from AI curiosity to real AI execution by building practical systems, projects, automations, and a strong LinkedIn presence. With a community of 300K+ builders, she brings real-world mentorship to every session.

300K+

Community Members

50+

AI Projects Shipped

Years in AI

Connect on LinkedIn Speak on WhatsApp

OUR LEADERSHIP TEAM

Our Leadership Team

Palani Ramasamy

CEO & Founder, Enterprise AI, Gen AI & Agentic Platforms

Mike Millard

Sr. VP, Agentic AI Strategy, Governance & Transformation

Mary Grygleski

Sr. VP, AI Evangelist - Enterprise AI & Architecture

Reshma Sriram

Director, AI Product Enablement, Enterprise Training & AI Adoption

ENROLLMENT & PRICING

Start Building Today

19 Oct – 13 Nov 2026 • Mon–Fri · 90 min a day • Limited Cohort

Live Cohort · Limited Seats

LuMay AI Masterclass

AI Fundamentals to Vibe Engineering: live classes, guided build labs & a deployed capstone.

$750

USD

per seat · full program + support week

20 live days: 8 classes + 12 guided build labs

1-on-1 mentor support & code reviews

3 portfolio projects + a deployed capstone

Week 5: support hours + LinkedIn branding

Exclusive builder community access

Official Certificate of Completion

Limited seats for the upcoming cohort. Secure yours today.

Secure checkout • Instant confirmation

FREQUENTLY ASKED QUESTIONS

Everything You Might Want to Know

Clear answers about who this program is for, what you will build, and the support you will get.

The program runs Mon 19 Oct to Fri 13 Nov 2026: live classes and guided build labs, Monday to Friday, 90 minutes a day, plus about 2 hours a week of self-practice. Week 5 is a post-program support week with support hours, doubt clearing, and LinkedIn branding.

Ready to Build with AI?