Master the 7-Pillar Applied AI Roadmap and land ₹25-50 Lakh AI Engineering jobs in 60 days
WITHOUT Learning ML Math, Expensive Bootcamps, or Starting From Scratch!
What You Will Learn: The 7 Pillars Of AI Engineering
Walk away with a complete roadmap and 90-day action plan to become an AI Engineer
Programming Fundamentals
Python basics, Jupyter notebooks, REST APIs with FastAPI, and version control essentials
LLM Fundamentals (Applied)
Understanding tokens, context windows, prompt engineering techniques (few-shot, chain-of-thought)
Frameworks: LangChain & LangGraph
Building chains, tools, memory management, and multi-agent systems with state machines
RAG (Retrieval-Augmented Generation)
Vector embeddings, document chunking, PGVector, hybrid search, multi-query, and reranking strategies
Production System Architecture
FastAPI backends, Redis & Celery for async jobs, Docker containerization, scalable architectures
Monitoring, Evaluation & Safety
LangSmith observability, ELK logging, RAG evaluation metrics, guardrails, PII filtering
Production Deployment
AWS Fargate, Docker orchestration, CI/CD pipelines, environment management for millions of users
By the end of this session, you'll walk away with:
Clarity on the order
Exactly which pillar to learn first, what to skip, and why most devs learn it backwards
A gap check on your skills
Which of your full-stack skills already transfer, and the few you need to add
A portfolio project blueprint
The one production-style project that signals "AI engineer" to recruiters
Interview-ready vocabulary
Talk about RAG, agents and evals the way hiring managers expect
A 90-day plan you can start Monday
Weekly milestones mapped to the 7 pillars
Who Is This Session for?
If you can ship a web app, you're closer to an AI role than you think.
The Full-Stack / MERN Developer
You ship real apps but keep seeing "AI experience preferred" on every ₹25L+ role.
The Backend Engineer
You already know APIs, queues and deployments. Now see where LLMs, RAG and agents fit in.
The Data Scientist
You know the models. Now learn to put them into production.
The Final-Year Student or Fresher
You want one serious, deployed project instead of a folder of tutorial clones.
Who's Teaching This?
A practitioner shipping production AI systems every day - not a course-seller teaching from a textbook
I'm Harish. I run OpenSlate.ai, an AI agency doing $10K MRR, where we build and ship real AI systems for clients every week. Everything in this roadmap is what I use in production - not theory I read about.
Before that I spent years building production AI at Samsung, Freshworks and Zoho, and I've consulted with 20+ organisations on their AI implementations. I've seen what actually breaks at scale, and what companies are really hiring for.
I've also taught 3,000+ developers through this exact transition - web developers with zero AI background who now build and ship AI systems. I know where people get stuck, because I've watched thousands of them get stuck in the same places.
Hear What Others Have to Say
All the way from senior Full-stack engineers and data scientists to even freshers
I took all the ServiceNow tickets, vectorized them, and made a searchable chatbot so support engineers can find solutions as quickly as possible... All the concepts I got from the course.
Literally anyone can write code with an LLM these days but understanding the architecture is what matters, and this course makes that clear. I applied the ingestion approach directly at my work and turned a fully manual process into one that now runs in an hour.
Everything on YouTube was scattered, and this course covered schema all the way to deployment. In an AI-engineering interview they asked me specifically about RAG implementation, and because I'd built it end-to-end, I could explain it confidently.
I'd tried learning RAG on my own with AI tools, but when I found this I could tell it was a serious course, not just a cash-grab. It's my first complete production RAG course, and it's making me think about switching into AI as my main career.
Everywhere it's just... they are just giving you the videos. But here it's an end-to-end project that can go to your portfolio - a good level of industry project, not just a dummy project for a random use case.
I found Harish on YouTube... I don't think there was such a detailed course, one project, on YouTube at that time. Every part teaches me something... how to set up front-end and back-end repositories, then how the database is designed. The pacing was good. It wasn't slow, it wasn't fast.
Register Now & Get These Bonuses
Worth ₹5,000+ in value, included free with your registration
90-Day Action Plan
Step-by-step roadmap with weekly milestones to become AI Engineer ready in 90 days
Resource Checklist
Curated list of best courses, docs, and tools for each pillar - save months of research
Masterclass Recording
Lifetime access to recording + slides. Rewatch anytime and share with your team
Frequently Asked Questions
Do I need AI experience to attend?
No! This masterclass is designed for web developers with zero AI experience. If you know one programming language (JavaScript, Python) and understand REST APIs, you're ready. I'll break down each pillar from fundamentals to advanced.
Is this live or pre-recorded?
This is a LIVE masterclass with real-time Q&A. You'll be able to ask me questions directly during the session. The recording will be shared with all attendees within 24 hours.
What if I can't attend the live session?
You'll get lifetime access to the recording, slides, and all bonus materials. However, I highly recommend attending live for the Q&A session where I answer specific questions about your situation.
What's your refund policy?
If you attend the live masterclass and feel you didn't get value, email us within 24 hours for a full refund. No questions asked. We're confident you'll find it valuable.
Your AI Engineering Career Starts Here
Don't let this opportunity window close. Secure your spot at early bird pricing before it increases to ₹499.