AI is moving fast. Your learning should too.
Past scattered tutorials and one-off prompting. Three physical learning paths — from understanding what agents are, to building workflows that connect to real systems, to thinking about them in production.
Start small.Go deeper when you're ready.
Three programs, one progression — not three disconnected courses. Fees paid on a shorter path can be adjusted against a longer one.
- Path 01 • 3 days
Agentic AI Starter
From₹3,999
Understand • Experience • Spot the opportunity
Beginners, students, managers and founders working out what agentic AI is actually good for.
The 3 days in full - Path 02 • 7 daysMost taken
Agentic AI Practitioner
From₹8,999
Build • Connect • Automate
Professionals, serious students and developers who want practical depth and something working at the end.
The 7 days in full - Path 03 • 12 days
Agentic AI Professional
From₹14,999
Architect • Orchestrate • Think production
IT professionals and learners who want real depth in architecture, orchestration and what it takes to ship.
The 12 days in full
Not another library of recorded videos.
The whole model is guided learning, doubts cleared the moment they appear, and support that outlasts the classroom.
- 01
Physical, face to face
Ask the question the moment it lands. See the explanation again. Nobody gets quietly stuck alone.
- 02
Beginner to professional
Three, seven or twelve days — you pick by where you're starting and how deep you want to go.
- 03
Learn until you're confident
Eligible learners can re-attend once, subject to seat availability and the published terms.
- 04
Support after class
30, 45 or 60 days of continued learning support, depending on the path.
- 05
Practitioner-led
Taught in the context of how this technology actually gets designed, integrated and used inside a business.
- 06
A real technical arc
LLMs, context, RAG, APIs, tools, workflows, memory, orchestration and production thinking.
Understand the shift
Build a clear mental model of AI, LLMs, agents, knowledge and tools — without getting buried in implementation.
From₹3,999
- 15–18 learning hours
- Low coding
- Beginner friendly
- 30-day support
Agentic AI Starter
- Day 1
Understand AI & LLMs
Generative AI, LLMs, tokens, embeddings, context, prompting, hallucinations and the basics of RAG.
- Day 2
Understand AI agents
Chatbots vs workflows vs agents. Reasoning, planning, memory, APIs, tools and context engineering.
- Day 3
Experience agentic AI
Knowledge-powered AI, tools, automation and the business cases they actually fit.
Build & automate
Agent design, RAG, tool calling, APIs and workflow automation — deeper, and still hands-on the whole way.
From₹8,999
- 35–42 learning hours
- Low to medium coding
- The balanced path
- 45-day support
Agentic AI Practitioner
- Day 1
AI & LLM essentials
LLMs, tokens, embeddings, context, prompting and where the models stop.
- Day 2
Agentic AI & context engineering
Agent architecture, objectives, reasoning, system prompts, structured outputs and guardrails.
- Day 3
Build your first agent
Goal, decision, tool choice, observation, answer — the loop, end to end.
- Day 4
RAG & knowledge-powered AI
Embeddings, retrieval, semantic search, vector search and grounding.
- Day 5
Tools, APIs & external systems
REST, JSON, function calling, and wiring an agent into applications that already exist.
- Day 6
Automation & agentic workflows
Triggers, actions, branching, validation, n8n-style workflows and human checkpoints.
- Day 7
Multi-agent & production foundations
Specialised agents, handoffs, orchestration, reliability and responsible use.
Architect AI systems
From foundations through richer RAG, connected agents, memory and multi-agent orchestration to production thinking.
From₹14,999
- 60–72 learning hours
- Medium technical depth
- The full pathway
- 60-day support
Agentic AI Professional
- Day 1
AI & LLM essentials
Generative AI, LLM mechanics, tokens, embeddings, transformers, context and limitations.
- Day 2
Agentic AI foundations
Goals, reasoning, planning, feedback loops, tools, actions and autonomy.
- Day 3
Prompt & context engineering
System prompts, structured outputs, few-shot patterns, context design and guardrails.
- Day 4
Building AI agents
Agent loops, tool schemas, decision logic and external actions.
- Day 5
RAG fundamentals
Document ingestion, chunking, embeddings, retrieval and grounding.
- Day 6
Knowledge-powered agents
Vector stores, retrieval quality, metadata and source-aware answers.
- Day 7
APIs, Tool Calling & MCP
Structured data, function calling, MCP servers and wiring an agent into services that already exist.
- Day 8
Agentic automation
Triggers, branching, validation, escalation and AI-enabled workflows.
- Day 9
Memory, state & context
Working memory, long-term memory, session state and experiences that persist.
- Day 10
Multi-agent systems
Specialised roles, delegation, handoffs, coordination and orchestration.
- Day 11
Production-ready thinking
Observability and evaluation: tracing agent runs, evaluation sets, reliability and human oversight.
- Day 12
Business & enterprise architecture
Integration patterns, scalable architecture choices and responsible deployment. Security and cost: access boundaries, data handling and what it takes to run.
The tools you'll actually touch.
Named, not implied. The hands-on days are built on what teams are shipping agents with right now — mostly open standards and open source, so what you learn here moves with you.
- Orchestration
LangGraph
Agent graphs with state you can see — branches, loops, retries, and a human checkpoint where one belongs.
- Tool protocol
MCP
The Model Context Protocol: one standard way to hand an agent tools, files and live systems, instead of a bespoke integration every time.
- Observability
Langfuse
Every run traced — prompts, tool calls, latency and spend — so a failure is something you open rather than something you guess at.
- Retrieval
pgvector
Embeddings stored beside your own data in Postgres, so grounding an agent doesn't start with a second database to run.
- Model gateway
LiteLLM
One interface in front of many models, with routing, fallbacks and a spend limit per key.
- Evaluation
promptfoo
Graded test cases for prompts and agents, so a change that quietly makes things worse is caught before it ships.
- Coding agent
Claude Code
An agent that reads a repository, makes the change and runs it — used as a tool, and studied as an example of the thing you are building.
Enrol earlier. Pay less.
The price rises as the cohort fills. It rewards committing early without discounting the program permanently — the last window is the real fee.
| Window | 3 days | 7 days | 12 days |
|---|---|---|---|
| Founding learner18–24 AugBest price, and every early benefit below. | ₹3,999 | ₹8,999 | ₹14,999 |
| Early bird25–31 AugDiscounted enrolment. | ₹4,499 | ₹9,999 | ₹16,999 |
| Standard1–7 SepRegular pre-launch pricing. | ₹4,999 | ₹10,999 | ₹18,999 |
| Last seats8–10 SepFinal enrolment window. | ₹5,999 | ₹11,999 | ₹19,999 |
Pay online — UPI or card — and your seat is confirmed the moment the payment goes through.
Enrol at this priceMore than classroom time.
Everything below exists to lower the risk of committing to the first cohort.
AI & LLM essentials pre-course
Start learning the moment you enrol, not the moment the room opens.
One free re-attendance
Rejoin an eligible batch once within six months, subject to seat availability.
30 / 45 / 60 days of support
Support runs on after the classroom does, and for longer on the longer paths.
The resource vault
Cheat sheets, diagrams, prompt patterns, architecture notes and a curated reading list.
Upgrade credit
Eligible fees carry over when you move Starter → Practitioner → Professional.
Priority alumni access
First invitations to refreshers, advanced sessions and community learning.
Three days shouldn't be the end of it.
Start on the Starter path if you're unsure. Continue into Practitioner or Professional when you want the depth. The upgrade credit is there so the first decision doesn't have to be the big one.
Find the path that fits.
3-day Starter • 7-day Practitioner • 12-day Professional