Generative AI Course in Madhapur
For engineers and builders in Madhapur, this course goes past prompting into the engineering behind production GenAI.
- Live cohorts, not recordings
- Practitioner-taught
- Community & placement
- Lifetime access
Enrol or get details
Tell me about your goals — I'll reply within 24 hrs.
Built for Madhapur builders
Every module ends with something working — a RAG pipeline, an agent, an eval suite — built live alongside peers from Madhapur and beyond. This goes past prompting into the actual engineering behind production GenAI.
Curriculum breakdown
Module 1: Prompt engineering and structured chains
Madhapur students learn structured prompt design and function calling, not just one-off prompt tricks.
Topics covered
- Prompt architecture and function calling
- Structured output validation
- Multi-step prompt chains
Module 2: RAG pipelines with vector databases
Building a working retrieval-augmented generation pipeline, end to end, as a Madhapur student.
Topics covered
- Chunking and ingestion strategy
- Vector database selection and indexing
- Retrieval quality evaluation
Module 3: Agents and tool use
Building an agent that uses tools reliably, for Madhapur students moving beyond single-turn prompting.
Module 4: Evals, guardrails and deployment
Shipping what you've built with monitoring and safety guardrails in place.
How the cohort runs
Format and schedule
Live, project-based cohort
Fully online, live over Zoom, for Madhapur learners and peers across every module.
Who this course is for
Engineers and builders
Madhapur engineers who want the architecture behind production GenAI, not just API basics.
Technical founders
Madhapur founders building an LLM-powered product who need to move past a fragile prototype.
Outcomes and support
Portfolio project
Madhapur students leave with a working RAG or agent project they can show employers.
Prerequisites
Basic Python recommended
The course focuses on architecture decisions for Madhapur students, not syntax fundamentals.
Note
Covers OpenAI, Anthropic (Claude), and open-source models, so Madhapur students aren't locked into one provider's mental model.
Why Madhapur builders choose Deepak Suhag
Taught by someone who ships production GenAI systems for clients — not a course built from documentation alone.
How it works
Simple, transparent process — from first contact to measurable results.
Enrol & Onboard
Instant portal access, cohort Slack invite, and full session calendar on day one.
Live Sessions
Weekly Zoom sessions with real campaign walkthroughs, live dashboard reviews, and Q&A.
Build & Get Feedback
Hands-on assignments on your own campaigns with direct 1:1 feedback from Deepak.
Graduate & Network
Industry certificate, alumni community, job board access, and ongoing placement support.
Tools & platforms
The exact stack I use daily across growth marketing, web development, AI, and automation — no guesswork, no vendor lock-in.
Why work with Deepak
Here's what makes this different from every other option in Madhapur.
Taught by a practitioner
Every module comes from live campaigns with real budgets — not textbook theory or outdated slides.
Live cohorts, not recordings
Ask questions in real time, get live feedback on your campaigns, and learn with a cohort of peers.
Practitioner-led curriculum
Real ad accounts, real case studies, real budgets — everything relevant to where you work, wherever that is.
Career-ready outcomes
Portfolio projects, alumni Slack, and direct referrals to companies actively hiring in your city.
Everything you need to know
Still have a question that isn't answered here? Reach out directly — I respond to every inquiry personally.
Ask a question01Do I need Python experience in Madhapur?
Basic Python is recommended — the course focuses on architecture, not syntax.
02Which LLM providers do you cover?
OpenAI, Anthropic (Claude), and open-source models.
03Is this available for Madhapur learners remotely?
Yes — the cohort runs fully online, live over Zoom.
04Do I get a project I can show employers in Madhapur?
Yes — a working RAG or agent project is part of the curriculum.
I started teaching because I was frustrated seeing marketers memorise theory they'd never use. Every lesson I teach comes from a live campaign, a real mistake, or a real win. You'll leave with skills you can use tomorrow morning.