Learn With Sarvesh
"Coming from a 25-year background in Visual Basic and Oracle, I was a complete beginner in the AI space. This journey with Python has been truly transformative."Faozia Mohiuddin25 years in VB & Oracle before AI
One complete, deployed AI system every 6 weeks. Learn from short recorded lessons at your own pace, then bring every doubt to a 3-hour live session every Sunday. Tech or non-tech — join any week.
LANGCHAIN · LANGGRAPH · CREWAI · RAG · MCP · FASTAPI · DOCKER · STREAMLIT · AZURE
▶ Start here — the AI roadmap, explained by Sarvesh
Welcome
"This program is for working professionals — tech or non-tech — who are ready to stop watching AI happen and start building it. You don't restart your career; you add AI on top of the experience you already have. Step by step, you'll build real systems you can show, explain and deploy with confidence. Welcome to Learn With Sarvesh, where learning turns into real-world AI systems."— Sarveshwaran R, Learn With Sarvesh
Instructors
Curriculum
No tutorial clones. Each 6-week cycle ships one production-style AI system — the kind companies actually pay for — built as a pipeline of four agents. Open a project to see the agent flow inside it.
Short recorded lessons, 8–15 minutes each. Concepts, setup and the full build walkthrough, at your own pace.
Build the project yourself, step by step, on your own schedule.
Every Sunday, 4:30 PM IST — a 3-hour live doubt-clearing session. Bring the error, leave with it fixed.
At the end of each 6-week cycle you have one complete system, deployed on Azure with a Streamlit front end.
Join any week — you're never "behind". Day one, you start the Foundations track. Then you pick up whichever project is running, at your own pace — and every Sunday's live session is open to your doubts, wherever you are in the work.
Ask a question in plain English and get an answer grounded in your company's own documents, with citations.
Every company has documents nobody can find. This is the most requested internal AI build in the market right now.
Read every incoming ticket, score how likely it is to blow up, and put the dangerous ones in front of a human first.
It saves money on day one and the ROI is easy to prove, which makes it the easiest project to get a business to pay for.
Not just triage. This one drafts the actual resolution, checks itself, and hands off to a human when it isn't sure.
The jump from a system that answers to a system that acts, which is exactly what an Agentic AI Engineer is hired for.
Read the SQL nobody documented, work out what feeds what, and answer "what breaks if I change this column?"
Almost nobody builds this in a portfolio. It shows you understand real data platforms, not just chatbots.
Watch what your competitors publish, work out how they position themselves, and find the gap you can own.
The buyer here is marketing or sales, not engineering, and non-technical buyers approve budget faster.
When production breaks at 2am, gather the signals, rank the likely causes, and draft the postmortem afterwards.
This is the one that convinces a hiring manager you've actually run something in production, not just built a demo.
A real lesson from Project 6: connecting MCP servers to Claude Desktop and AI agents with FastMCP. Same style, same depth as everything inside.
Enroll now — ₹19,999The gap
Many courses teach AI tools and step-by-step tutorials. Building real AI systems requires deeper understanding than that.
Core philosophy
"Tools change. Mental models last."
Who this is for
Tech or non-tech, everyone starts on the same Foundations track — so nobody is left behind on day one.
This is a skills-first program.
Format
Everything is recorded, so you learn and build whenever it suits you. Once a week, you bring your doubts to a live room and leave unblocked.
Short recorded lessons for every concept and every build step. Watch any time, rewatch as often as you need.
Every Sunday, 3 hours live — 4:30 PM IST · 3:00 PM Dubai · 7:00 AM New York. Bring the error, leave with it fixed.
Miss a Sunday? Watch the recording — someone else's doubt is often the exact one you had.
No batch start dates. A new project starts every 6 weeks, and every project comes round again.
Every future cycle for two years — roughly 17 cycles — while the field keeps moving.
Stay in touch between Sundays — updates, instructions and fellow learners building the same projects.
Bonus inclusions
Everything you get when you enroll in the AI Engineer Ready Program — beyond the six core projects.
Basics · 6 hrs · Beginner friendly. Master Python from scratch for AI, Data Science & projects.
8 hrs · Intermediate level. Build on your Python skills with advanced concepts, projects & real-world applications.
Live session · 24 hrs. Build real-world AI projects with mentorship from Sarvesh.
Recordings, slides, resources, and assignments from past cohorts.
Stack
The same stack applied AI teams build with — FastAPI behind, Streamlit in front, deployed on Azure.
Career outcomes
"AI Engineer" has split into distinct roles — and companies pay a premium for people who can build the whole system.
Entry band with a real GenAI project portfolio. The base role every other one builds on.
₹18–28 LPA in the first 2 years, ₹28–55 LPA at 3–6 years. Your domain experience is the entry ticket.
₹8–15 LPA entry, ₹15–30 LPA mid-level. The newest title, with the thinnest talent pool.
Premium over an equivalent developer profile. The highest hiring volume of any AI role.
Entry band for the role you grow into after 1–2 years building AI systems.
India, 2026 salary bands. Sources: Taggd · EICTA (IIT Kanpur) · Recrew · OwnYourCareer · WorthvieW · NovelVista · Futurense · ERI SalaryExpert.
Proof
"Coming from a 25-year background in Visual Basic and Oracle, I was a complete beginner in the AI space. This journey with Python has been truly transformative."Faozia Mohiuddin25 years in VB & Oracle before AI
"Before joining this program, I had no clear direction in AI. This course completely changed how I understand and approach AI."KiranNo tech background
"After 30+ years in non-tech corporate industries, I wanted to transition into tech and work for myself. Learning here made a daunting transition simple and approachable."Michael AwanayahNow building his own tech company
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"Before this cohort, I thought AI was just prompting models. Now I design complete AI systems where memory, tools, and retrieval work together to build real-world applications."
"Earlier AI felt like magic. Now I understand how LLM systems work and I can build RAG pipelines and agent workflows with confidence."
"This cohort gave me the confidence to build AI systems independently. Building AI agent tools and multi-client server workflows was the most exciting part."
"The course provided practical insights into how AI can be applied in real-world scenarios. The AI Agents module was my favourite."
"This cohort shifted my focus from just models to the importance of retrieval and context. Multi-agent orchestration showed how AI systems collaborate to solve complex tasks."
"This cohort helped me clearly understand how modern AI systems work. The hands-on projects made it easier to learn how LLMs, RAG, and AI agents can be applied to real-world problems."
"The course provided a clear and practical understanding of building AI systems. Learning how to connect prompts, tools, and retrieval pipelines was extremely valuable."
"This cohort gave me strong exposure to agentic AI concepts and modern LLM frameworks. The structured modules and projects helped me build confidence in developing AI applications."
"This program helped me build real-world AI applications like resume analyzers, chatbots, and document summarizers using LangChain and RAG pipelines."
"This program provided both strong theoretical understanding and hands-on experience through real projects. Learning RAG systems and agent orchestration significantly improved my confidence."
"This cohort helped me transition from traditional programming into AI development. I now understand how to design intelligent AI agents that can reason, use tools, and solve complex problems."
"I learned how modern AI systems work using LLMs, RAG, LangChain, MCP, and LangGraph. The LangGraph module helped me understand how AI workflows plan, execute, and validate tasks."
"This program provided both a deep understanding of AI systems and hands-on experience through industrial-level projects. Learning about LangChain and building voice agents significantly improved my confidence in developing real-world AI solutions and helped me in my current work."
Straight from the chat
Real reactions captured during live sessions — names blurred for privacy.
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In their own words
Enrollment details
Register now
Build real AI systems and develop the engineering mindset required to deploy production-ready AI applications.
Program fee
₹19,999·$259
program value ₹1,00,000
Secure checkout via Razorpay — pick whichever currency matches where you're paying from. All payments are final — no refunds once paid (refund policy).
After you pay
Not ready to enroll yet?
The whole journey on one road, then for each of the six projects: what you build, agent by agent, and the step-by-step path to get there. A PDF you can keep.
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