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IIT Kharagpur campus

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24
Weeks
9
Modules
1
AI Product
  • Build one AI product end-to-end, from opportunity to deployment
  • AI-native product management — design, LLMs, RAG and agentic AI
  • Evaluate AI like a product leader — red teaming, metrics, model evaluation
  • AI economics and GTM — pricing, token economics, go-to-market
  • India-first AI product design — DPDP, India Stack, AI compliance
  • Graduate with proof — a working prototype plus 7 portfolio artefacts
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MODULE 1

AI Product Opportunity Discovery

  • AI product landscape — categories, business models, AI-native vs AI-enhanced
  • AI Suitability Matrix — probabilistic, learnable, recoverable, data-rich dimensions
  • TASQ checklist — task ambiguity, scale, quality tolerance as a first-pass filter
  • AI Opportunity Canvas — data richness, failure recoverability and feedback loops
  • Feasibility assessment — model capability, costs, data and regulatory risk
  • Build vs buy vs prompt decision framework
MODULE 2

AI-Native Product Design

  • Behaviour specifications — constraints, failure modes, fallback paths, confidence thresholds
  • AI PRDs — eval criteria, hallucination risk tiers, data and guardrail specs
  • Trust architecture — transparency, confidence calibration, user control
  • Copilot–autopilot spectrum as a product design decision
  • AI UX/UI — chat, inline suggestions, ambient intelligence, co-creation canvas
  • Products vs services vs platforms — platform readiness
MODULE 3

AI & GenAI Fluency

  • LLM architecture intuition — transformers, embeddings, tokenisation
  • Foundation model landscape and how to evaluate one for a product
  • Token economics in INR — cost per query at scale
  • Prompt engineering as product design
  • Build vs buy vs prompt vs fine-tune decision framework
  • Multimodal AI — vision, voice and document models in product context
MODULE 4

AI Prototyping & Rapid Validation

  • Prompt-to-app prototyping with live LLM API integration
  • Multi-turn conversation design and structured output handling
  • Structured peer review using an AI product review rubric
  • Prototype audit — documenting production gaps
  • Production handoff specification — architecture, security, effort
  • Prototype-to-production gap analysis and stakeholder presentation
MODULE 5

AI Systems & Agentic Design

  • RAG architecture — chunking strategy, vector databases, retrieval failure modes
  • Agentic workflows — tool use, planning, multi-agent orchestration
  • MCP as an integration standard
  • Autonomy taxonomy for designing agent boundaries
  • India Stack as agent infrastructure — UPI, Aadhaar, Account Aggregator
  • Data flywheel design and infrastructure literacy for PMs
MODULE 6

AI Evaluation & Red Teaming

  • Test dataset construction — gold, operational, adversarial, safety sets
  • RAGAS metrics and LLM-as-judge methodology
  • Quality gates — launch, target and aspirational thresholds
  • Adversarial red teaming — prompt injection, jailbreaks, adversarial inputs
  • Hallucination classification — factual, contextual, logical risk tiers
  • Ship / no-ship decision protocol based on evaluation evidence
MODULE 7

AI Analytics & Experimentation

  • Four-tier AI metrics model — model, system, product and business metrics
  • AI-native metrics — acceptance rate, override rate, cost per correct output
  • A/B testing for non-deterministic outputs — shadow deployment, interleaving
  • Model drift detection — monitoring and retraining triggers
  • Feedback loop design as product operations
  • Instrumentation spec and experiment design for AI products
MODULE 8

AI Product Economics & Go-to-Market

  • LLM unit economics — token, infrastructure and orchestration costs in INR
  • The whale-user problem and cost governance strategy
  • AI pricing playbook — consumption, outcome and seat-based models
  • GTM for AI trust challenges — trust-first positioning, enterprise sales
  • India market channels — WhatsApp, ONDC, GeM, IndiaAI Mission
  • Change management and stakeholder alignment for AI products
MODULE 9

AI Operations, Safety & Compliance

  • DPDP Act 2023 — consent architecture, data minimisation, purpose limitation
  • NIST AI RMF — risk tiering, documentation, governance framework
  • EU AI Act risk tiers and prohibited use cases
  • RBI FREE-AI framework for financial AI products
  • Production monitoring, drift response, go/no-go escalation
  • AI incident response protocol and regulatory notification
CAPSTONE

The Proof — IIT Faculty Defence

  • AI Opportunity Brief — problem, suitability, feasibility, competitive landscape
  • AI Product Specification Pack — behaviour spec, PRD, trust architecture
  • Model Selection Brief — candidates evaluated with INR cost projections
  • Working AI prototype plus production handoff specification
  • System architecture, evaluation framework and red-teaming evidence
  • Live model-drift crisis injection — go/no-go decision before the faculty panel

A Portfolio of Real AI Products

Portfolio of real AI systems you can demonstrate, explain, and extend

AI Opportunity & Feasibility Brief

Assess AI opportunities through problem framing, feasibility analysis, and market validation.

Capstone: Build, Defend & Launch an AI Product

Your signature AI product portfolio, built and shipped by you.

1
AI Product
7
Portfolio Artefacts
IIT
Faculty Defence
  1. Discover — Validate an AI opportunity and define the product vision.
  2. Design — Create AI PRDs, behaviour specs, and system architecture.
  3. Build — Develop a working AI prototype with LLMs and agentic workflows.
  4. Evaluate — Test quality, safety, performance, and AI metrics.
  5. Launch — Build the business case, GTM strategy, and governance plan.
  6. Defend — Present your AI product before an IIT Kharagpur faculty panel.
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Campus graduation

How will upGrad support you?

100% live sessions by IIT Kharagpur faculty and industry experts
Live weekend session schedule
Built-in practice and coding console
Industry-oriented projects for real-world exposure
Doubt-resolution sessions through the discussion forum
Telegram channel for learner communication
Query assistance whenever you're stuck
Learning experience and completion support
1:1 career coaching
Career preparation modules
AI-powered profile builder
High-impact networking events and mock interviews
Discussion forum to resolve doubts and learn from peers
Meet and network with peers at the award ceremony at IIT Kharagpur

EPGC in AI Products & Services Course Fee

6 Months · Eligibility: Graduation with a minimum of 50% marks

₹0 - ₹0 Course Fee Range
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