Learn Production AI.
Ship a Live Product.
in 30 Days
Walk away with a job-winning portfolio project hiring managers can actually test. Master the entire AI stack and System Design with a complete production system as complex as Google's NotebookLM.
Built for Engineers, Not Beginners
This program works best if this sounds like you
You've been a software engineer for atleast 1 year
You've tinkered with LangChain or made a few LLM API calls on weekends
You're 3+ months into learning applied AI - but everything you've built still feels like a toy, not a product
You're a Frontend, Backend, Full-Stack, ML/AI, Data, QA, or Salesforce engineer - your stack doesn't matter, your engineering fundamentals do
Not for you if: you're brand new to programming, or you're looking for ML theory and math - this is hands-on, production-focused engineering.
So Why Are You Still Stuck?
It's not a knowledge problem. It's a proof problem.
Your Jupyter notebook isn't a portfolio
A hiring manager asks what you've deployed. Not what you've learned - deployed. And your notebooks don't count as an answer.
Toy projects all look the same
Every applicant has a Streamlit + ChromaDB demo. Recruiters can smell a weekend project. Nothing about it proves you can handle real traffic, errors, or scale.
Figuring it out alone takes months
Async pipelines, guardrails, evals, deployment - the production patterns aren't in the docs. You could stitch them together from 40 free youtube videos. Or lose 6 months going in circles.
Meet the System You'll Ship
Your own NotebookLM - deployed on AWS, live at a real URL, with your name on the repo.
Async ingestion pipeline
Watch documents flow through S3 → partitioning → chunking → vectorization in real time. Powered by Celery + Redis, not a blocking script.
4 retrieval strategies
Simple vector, hybrid, multi-query, and multi-query hybrid - switchable per chat, so you learn when each one wins.
Reranking on demand
Toggle rerankers in configuration and watch answer quality change. This is the stuff interviewers actually ask about.
Cited, streamed answers
Chat scoped to each project's documents, with sources - not hallucinated summaries.
Production guardrails
Input validation against prompt injection, toxicity, and PII - the layer toy projects never have.
Deployed on AWS Fargate
A real URL a hiring manager can open, click, and test - the difference between "I learned RAG" and "I shipped RAG."
Master the Full Stack Real AI Engineers Use
Frontend Stack
Backend Stack
Database & Storage
AI/ML Stack
Deployment & Infrastructure
Monitoring & Observability
Complete Course Curriculum
Try it, risk-free
I'm confident that you'll love this course. But if it's not the right fit, no worries! Get a refund within 30 days.
Master Production AI for Less Than a Weekend Course
Most bootcamps charge ₹50,000+ for generic courses. This teaches you the stack companies are hiring for in 2026.
What's Included
Real Results From Real Students
Read their transformations and success stories
How it works
Get instant access
Enroll and start learning today. The program is currently open. No application required. Join instantly and begin your journey whenever you're ready.
Explore the academy
Log in and get started. Once enrolled, you'll unlock the full platform, including the curriculum, community, and support resources. No need to wait for a cohort to start.
Learn and build
Follow the structured program. Work through weekly modules, apply concepts in practical lab exercises, and build a complete AI application using our production framework.
Common Questions
Everything you need to know before enrolling
Do I need AI or machine learning experience?
No. This is an applied AI course using APIs - no machine learning background needed. If you know basic Python and how REST APIs work, you're ready. Perfect for web developers transitioning to AI engineering.
How long does it take to complete?
Yes. The course is designed for working professionals. Most students dedicate 1-2 hours daily and complete it in 4 weeks. All videos are focused and to the point. You can pause, rewind, and learn at your own pace. Several students have completed it while working 50+ hour weeks.
What if I get stuck?
You get direct access to me (Harish). Post your questions in the community or DM me directly - I personally respond within a few hours, not days. Plus, you're joining 3,000+ developers who actively help each other. Most technical questions get answered within 2-3 hours.
Is this production-grade code or just tutorial code?
This is production code that you can deploy to real users. We follow industry best practices: proper error handling, logging, testing, security, database migrations, environment configuration, and CI/CD pipelines. This isn't "works on my laptop" code - it's code you'd see in a $200K/year engineer's GitHub.
How is this different from other GenAI courses?
Most courses teach you how to use LangChain in a Jupyter notebook with ChromaDB. We build a full-stack production system from scratch - frontend, backend, database, auth, async processing, deployment. You'll understand WHY things work, not just copy-paste code. This is the difference between "I followed a tutorial" and "I built a production system."
What if the technology changes? Will the course be updated?
Lifetime access includes all future updates. As concepts evolve, I update the course. Recent additions: LangGraph 1.0 workflows, advanced evaluation frameworks, and Kubernetes deployment. The architectural principles remain constant - specific tools may change, but you'll understand the fundamentals deeply enough to adapt.
Will this actually help me get hired?
I can't guarantee you a job (no one honestly can). But I can guarantee you'll have a portfolio project that makes recruiters respond. Several students have landed AI engineer roles and consulting gigs by showcasing this exact project. One student negotiated a ₹12L increase by demonstrating this in their interview. The system you build here is more impressive than what 90% of "AI engineers" have on their GitHub.
Do I get a certificate?
No, and here's why: certificates from online courses mean nothing to employers. Your GitHub repository with a working production RAG system is worth 100x more than any certificate. We focus on building proof of work that speaks for itself - not decorative PDFs for LinkedIn.
Is the course in English? Will I understand the accent?
Yes, all content is in clear English. I'm Indian, so my accent is familiar to most Asian learners. Videos have adjustable playback speed if you need to slow down. Code is universal - even if you miss something in audio, the written code and comments are comprehensive.
Do I need expensive tools or services?
No. We use free tiers of AWS, Supabase for development. You might spend ₹500 or 5$ on API credits while building, but nothing close to expensive.
Can I build my own projects after this?
Absolutely. That's the point. You'll understand the architecture so deeply that you can adapt it to any RAG use case - legal document search, customer support, research tools, whatever you want to build.
What's your refund policy?
30-day money-back guarantee, no questions asked. If you're not satisfied for any reason, email us within 30 days for a full refund.