In 4 weeks, become the engineer who actually ships production GenAI.
A high-touch live program for engineers who want more than tutorials. Build, deploy, and defend four real systems — LLM apps, RAG pipelines, autonomous agents, and a safety-hardened multi-agent capstone — under the eye of practitioners who've shipped them.
Application takes 2 minutes · We reply within 24 hours
Built for engineers, not tourists.
You've played with ChatGPT and read the LangChain docs. You've maybe shipped a toy demo. But every "real" GenAI feature you try to build at work hits the same walls — hallucinations, latency, cost spirals, prompt injection, no observability.
This program is the opposite of a YouTube playlist. You get a compressed, opinionated path from prompt to production — taught live, with code reviews on what you actually build.
Software / ML engineers
Already shipping code, ready to make GenAI a serious part of your stack.
Technical founders
Building an AI product and tired of guessing whether your architecture will hold up.
Senior devs eyeing AI roles
Want a portfolio of 4 real systems you can demo in interviews — not Jupyter notebooks.
Teams modernising internal tools
Add 1–2 of your engineers; they bring back blueprints your whole team can use.
You'll have shipped systems most "AI engineers" only talk about.
Streaming LLM app
Production-grade chatbot with streaming, retries, structured outputs and a reusable prompt library.
RAG pipeline (DocuMind)
Multi-format ingestion, smart chunking, vector store, semantic search and re-ranking.
Tool-using agent
ReAct-pattern research agent with planning, memory, function calls and graceful failure handling.
Compliance-hardened capstone
Multi-agent system with PII protection, prompt-injection defence, rate limiting and monitoring.
A 4-week path from prompts to production.
Every week ships working code. No fluff, no toy demos — you build systems you can deploy on Monday.
LLMs & Prompt Engineering
Master the core mechanics of Large Language Models and how to control them effectively.
Key Concepts
- LLM Architecture: Tokens, Context Windows, Temperature
- API Mastery: OpenAI, Claude, and Gemini integration
- Prompt Engineering: Chain-of-Thought, Few-Shot, ReAct
- Streaming responses & UX optimization
Hands-on Labs
- Build 'SupportGenie v0.1' — basic chatbot
- Implement streaming & error handling
- Create a reusable Prompt Library
RAG Systems & Vector Databases
Ground your AI in reality by building Retrieval-Augmented Generation systems.
Key Concepts
- Document processing: PDF/Text chunking strategies
- Vector embeddings: from text to numbers
- Vector stores: implementing ChromaDB
- Semantic search algorithms & re-ranking
Hands-on Labs
- Lab 3: Multi-format Document Processor
- Lab 4: Building a Semantic Search Engine
- Lab 5: Complete RAG Pipeline for 'DocuMind'
Autonomous Systems
Create sophisticated AI agents that use tools, decide, and complete complex multi-step tasks.
Key Concepts
- Agent Fundamentals: Agents vs Chatbots, the Observe → Think → Act loop
- Function calling with OpenAI & Claude, multi-tool agents
- Agent memory: short-term, working & long-term
- ReAct pattern, task decomposition & planning
- Agentic RAG: combining agents with retrieval
- Frameworks: LangChain, CrewAI, AutoGPT
- Multi-agent coordination & enterprise deployment
Hands-on Labs
- Lab 6: Agent fundamentals & tool calling — 6+ design patterns
- Lab 7: Memory & planning — conversation history & ReAct workflows
- Lab 8: Advanced agent systems — production research agent with error handling
Production Safety & Compliance
Implement safety, governance, and compliance to make AI systems enterprise-grade.
Key Concepts
- Input & output filtering: validation and sanitization
- Prompt-injection prevention
- PII protection: detection & handling
- Bias detection & mitigation
- Rate limiting & access control
- Regulatory compliance: GDPR, SOC2
- Production deployment: monitoring, logging & incident response
Hands-on Labs
- Implement comprehensive input/output guardrails framework
- Build 'SafeAI' — production compliance layer with PII protection
- Final Capstone: deploy enterprise-ready multi-agent system
It's not a course. It's a workshop.
10 seats. Zero hiding.
Cohorts capped at 10 engineers so you get real airtime, real feedback, and real accountability.
Code reviewed 1:1
Submit your labs and get line-by-line review from practitioners — the way you'd learn at a great team.
Live, not pre-recorded
8 live working sessions on Zoom. Every doubt answered live. Recordings if you miss one.
Production-first content
Streaming, evals, observability, cost control, safety — the boring 80% that separates demos from products.
Modern stack, vendor-neutral
OpenAI · Claude · Gemini · ChromaDB · LangChain · CrewAI · AWS Bedrock · Guardrails AI.
Capstone you can ship
Walk out with a deployed multi-agent system — and the playbook to repeat it at work.
"Most engineers don't need another tutorial. They need someone to watch them ship a real system end-to-end and tell them where it will break in production. That's what this program is."
— Lead Instructor, Gen AI Guru
From the same instructors. 4,000+ verified reviews.
You won’t find these reviews on a sales page — they’re live on Udemy across our 7 courses, written by engineers exactly like you.
“Excellent course! Game-changer for me. The course shows you how to extract the maximum from agents, working intelligently — with the explanation needed to understand the ecosystem.”
“I am an experienced developer but couldn't follow examples in the official docs. In this course the instructor explains how everything in a pipeline fits together. Highly recommended — key knowledge not available elsewhere.”
“Well-structured course material summarising the various techniques to improve AI guardrails. The instructor is responsive and answers queries patiently.”
“Comprehensive learning with hands-on. Well presented and the pace was apt — actually covers the Amazon Bedrock platform components in real depth.”
Everything you need. Nothing you don't.
- ✓ 8 live cohort sessions on Zoom (4 weeks)
- ✓ 8 hands-on labs across LLMs, RAG, Agents, Safety
- ✓ 1:1 code reviews on every lab you submit
- ✓ Capstone: deployed multi-agent system
- ✓ Private Slack with the cohort & instructors
- ✓ Lifetime access to recordings & updates
- ✓ Alumni-only future cohorts & office hours
How is this different from Udemy or YouTube?
Live cohort, capped at 10, with 1:1 code review. The accountability and feedback loop is the product — not just the content.
What's the time commitment?
About 6–8 hours/week: 2 live sessions plus lab work. Sessions are recorded if you miss one.
Do I need GPU access?
No. We use OpenAI, Anthropic, and Gemini APIs plus open vector stores like ChromaDB. A laptop is enough.
When does the next cohort start?
Cohorts are small and start regularly. Apply and we'll send you the next available intake date.
10 seats. One cohort. One decision.
If you're serious about shipping production GenAI in 2026, apply to the next cohort. Pricing is shared 1:1 after we confirm you're a fit.