AI5 ACADEMY PROFESSIONAL CERTIFICATE · A TGC INDIA INITIATIVE · UPDATED SEPTEMBER 2026
AI Product Management Professional Program Course
Who should join: Product managers · Business analysts · Founders and product owners
12 weeks · Online + Offline · 12 practical projects
Tools: ChatGPT · Claude · Gemini · Perplexity · Figma AI · Lovable
Build: AI Product Foundations & Role Map · AI Opportunity & Feasibility Study
Want syllabus, fees and batch timing?
Talk to AI5 Academy counsellor and get course details based on your background.
12-WEEK AI PRODUCT MANAGEMENT PROFESSIONAL PROGRAM · 36 LIVE SESSIONS
Build AI product strategy, discovery, PRDs, prototypes, RAG and agent workflows, evaluation plans, launch systems and a career-ready capstone.
Built as a 12-week professional route, not a compressed short course. Learners get time to work through discovery, PRD, roadmap, prototype, RAG, agents, model decisions, evaluation, launch planning and a portfolio capstone.
12 Weeks36 Live Sessions3 Sessions / Week60–90 Minutes / Session12 Portfolio OutputsPortfolio Capstone
22+years in training
20,000+learners across TGC
5classroom locations
Live onlinejoin from anywhere
NEXT START OPTIONS
Choose a live batch.
COURSE OVERVIEW
What this course
is built to do.
A 12-week professional program for taking an AI product from user problem and strategy through PRD, roadmap, no-code prototype, RAG, agents, model/API decisions, evaluation, launch planning and a career-ready capstone.
Each module combines a live trainer demonstration, guided lab, assignment and review before the next stage.
CONNECTED CAREER DIRECTIONS
AI Product ManagerAI Product OwnerProduct Strategy AssociateAI Product Operations Analyst
IS THIS COURSE RIGHT FOR YOU?
Choose it for the right reason.
You manage or plan digital products
You need strong AI PRDs, roadmap and model decision skills
You want enough time for discovery, RAG, agents, evaluation, launch and portfolio practice
YOUR LEARNING ARC
From guided foundation to finished work.
Discover
Find the user problem, product boundary, business value and AI feasibility.
Specify
Write AI PRDs with data, model, workflow and acceptance checks.
Prototype
Create AI UX, no-code, RAG and agent product prototypes.
Launch
Plan evaluation, analytics, GTM, pricing and career-ready product evidence.
INDUSTRY TASKS
Practise the work, not only the tool.
- AI Product Foundations & Role Map
- AI Opportunity & Feasibility Study
- User Research, Persona & JTBD Pack
- AI Product Strategy & Roadmap
- AI PRD with Data, Model & Acceptance Criteria
- AI UX Flow, Conversation & Wireframe Prototype
- No-Code AI Product Prototype
- RAG Knowledge Product Prototype
- Agentic AI / MCP Workflow Prototype
- Model, API, Cost & Build-vs-Buy Decision Record
- AI Evaluation, Analytics & Risk Scorecard
- AI Product Launch & Portfolio Capstone
PRO
LED
LED
YOUR TRAINING TEAM
Learn from experienced working professionals.
Live demonstrations, guided practice and direct project feedback are part of the course. Trainers update examples and tool coverage as professional practice changes.
WHAT YOU WILL BE ABLE TO DO
Course outcomes
01
Frame a sound AI product opportunity
A scored opportunity, user research pack and feasibility study.
02
Write testable AI product requirements
An AI PRD covering users, data, model, workflow, acceptance checks and fallbacks.
03
Prototype AI, RAG and agentic product experiences
AI UX, no-code, RAG and Agentic AI/MCP prototypes with failure and correction paths.
04
Choose models and measure product quality
A model decision record, evaluation plan, risk scorecard and economics view.
05
Plan launch and career presentation
A launch-ready 12-week capstone case study suitable for portfolio and interviews.
TAKE THE NEXT STEP
Need fees, syllabus or the right batch?
An AI5 Academy advisor can help you compare mode, schedule and starting level.
DETAILED COURSE FLOW
12 learning modules
A 12-week professional program to take an AI product from problem discovery to PRD, prototype, RAG, agents, model decisions, evaluation, launch planning and a career-ready portfolio case.
Week 1 — Product Management foundations for AI products
Understand the PM role, the product lifecycle and how AI products differ from standard software.
CORE TOPICS
- Product manager responsibilities
- Product lifecycle and business goals
- AI product categories and examples
- Stakeholders in AI products
- How AI changes discovery, delivery and launch
GUIDED PRACTICE
Map one AI product idea against users, business goals, stakeholders and product risks.
MODULE DELIVERABLE
AI Product Foundations & Role Map
Week 2 — AI opportunity discovery and feasibility
Select AI product opportunities that are useful, possible and commercially sensible.
CORE TOPICS
- Market and competitor research
- Opportunity scoring
- AI feasibility and data availability
- Risk filters and constraints
- Business value and success measures
GUIDED PRACTICE
Compare three AI product opportunities and select one for the capstone route.
MODULE DELIVERABLE
AI Opportunity & Feasibility Study
Week 3 — User research, personas and JTBD
Turn user evidence into a clear problem statement and product direction.
CORE TOPICS
- Interview and survey planning
- Persona and journey mapping
- Jobs To Be Done
- Pain-point mapping
- Assumptions and evidence logs
GUIDED PRACTICE
Create a user research pack with personas, JTBD and a problem statement.
MODULE DELIVERABLE
User Research, Persona & JTBD Pack
Week 4 — AI product strategy and roadmap
Convert research into a product strategy, MVP scope and roadmap.
CORE TOPICS
- Product vision
- Target users and positioning
- Value proposition
- Prioritisation and MVP boundaries
- Roadmap and stakeholder alignment
GUIDED PRACTICE
Prepare a strategy brief and roadmap for the selected AI product.
MODULE DELIVERABLE
AI Product Strategy & Roadmap
Week 5 — Product requirements and AI PRDs
Write requirements that design, engineering and business teams can test.
CORE TOPICS
- AI PRD structure
- User stories and acceptance criteria
- Data and model requirements
- Edge cases, fallback states and human review
- Release readiness checks
GUIDED PRACTICE
Write a complete AI PRD for one product feature or workflow.
MODULE DELIVERABLE
AI PRD with Data, Model & Acceptance Criteria
Week 6 — AI UX, wireframes and conversation design
Design how users direct, inspect, correct and trust an AI feature.
CORE TOPICS
- AI UX patterns
- Prompt and interaction surfaces
- Onboarding, trust and uncertainty
- Empty, error and correction states
- Figma AI and wireframe review
GUIDED PRACTICE
Create wireframes for normal, error and correction paths.
MODULE DELIVERABLE
AI UX Flow, Conversation & Wireframe Prototype
Week 7 — No-code and AI-assisted prototyping
Convert the product idea into a demo that can be tested and explained.
CORE TOPICS
- Lovable and no-code prototyping
- Workflow mockups
- Test data and demo scripts
- Prototype feedback loops
- Stakeholder demo preparation
GUIDED PRACTICE
Build or simulate a clickable AI product prototype.
MODULE DELIVERABLE
No-Code AI Product Prototype
Week 8 — GenAI, RAG and knowledge-product planning
Plan products that answer from approved knowledge rather than unsupported model memory.
CORE TOPICS
- RAG use cases and knowledge boundaries
- Documents, chunking and embeddings
- Vector search and retrieval quality
- Citations, freshness and permission checks
- Hallucination controls
GUIDED PRACTICE
Design and prototype a knowledge-backed product experience.
MODULE DELIVERABLE
RAG Knowledge Product Prototype
Week 9 — Agents, tool use and MCP for product managers
Understand when an AI product should use tools, actions, memory and connected systems.
CORE TOPICS
- Agent workflows and task boundaries
- Tool calling and MCP concepts
- Approval gates and permissions
- Memory and activity logs
- Failure, misuse and escalation cases
GUIDED PRACTICE
Map an agentic product workflow with permissions, fallbacks and tests.
MODULE DELIVERABLE
Agentic AI / MCP Workflow Prototype
Week 10 — Model, API and build-versus-buy decisions
Choose models, vendors and technical paths using product trade-offs.
CORE TOPICS
- Model and vendor selection
- API basics and structured outputs
- Privacy, security, latency and cost
- Build, buy and partner decisions
- Working with engineering teams
GUIDED PRACTICE
Create a model/vendor decision record for the capstone product.
MODULE DELIVERABLE
Model, API, Cost & Build-vs-Buy Decision Record
Week 11 — AI evaluation, analytics, risk and economics
Measure product quality, behaviour, risk and business impact before launch.
CORE TOPICS
- Task success and quality scoring
- Human review and feedback loops
- Activation, retention and funnel metrics
- Failure logs and improvement decisions
- Cost per task and product economics
GUIDED PRACTICE
Build an evaluation, risk and metrics plan for the prototype.
MODULE DELIVERABLE
AI Evaluation, Analytics & Risk Scorecard
Week 12 — Launch, GTM, capstone and portfolio
Package the work as credible AI PM portfolio evidence.
CORE TOPICS
- MVP rollout and onboarding
- GTM, messaging and pricing
- Pilot design and customer feedback
- Capstone case-study structure
- PM interview story and portfolio review
GUIDED PRACTICE
Present the final AI product case from user problem to launch plan.
MODULE DELIVERABLE
AI Product Launch & Portfolio Capstone
Want syllabus, fees and batch timing?
Talk to AI5 Academy counsellor and get course details based on your background.
HOW THE TRAINING WORKS
Learn it. Apply it. Get it reviewed. Improve it.
Every important skill moves through explanation, demonstration, guided use and independent application. Trainer feedback is used to revise the work before it becomes part of the final portfolio.
Concept briefing
The trainer explains the principle, use case, limitations and the quality standard expected.
Live demonstration
A complete task is demonstrated while the trainer explains decisions, checks and common mistakes.
Guided lab
Learners repeat the method with support, ask questions and correct problems during the session.
Applied assignment
The same method is used on a different brief so the learner must make independent decisions.
Review and revision
Work is checked against a rubric, revised after feedback and prepared for project presentation.
PROGRESS IS CHECKED THROUGHClass exercisesModule deliverablesProject reviewsFinal capstone presentation
PORTFOLIO WORK
Projects you can show
AI Product Foundations & Role Map
Plan, produce, test and present a finished piece with trainer feedback.
AI Opportunity & Feasibility Study
Plan, produce, test and present a finished piece with trainer feedback.
User Research, Persona & JTBD Pack
Plan, produce, test and present a finished piece with trainer feedback.
AI Product Strategy & Roadmap
Plan, produce, test and present a finished piece with trainer feedback.
AI PRD with Data, Model & Acceptance Criteria
Plan, produce, test and present a finished piece with trainer feedback.
AI UX Flow, Conversation & Wireframe Prototype
Plan, produce, test and present a finished piece with trainer feedback.
No-Code AI Product Prototype
Plan, produce, test and present a finished piece with trainer feedback.
RAG Knowledge Product Prototype
Plan, produce, test and present a finished piece with trainer feedback.
Agentic AI / MCP Workflow Prototype
Plan, produce, test and present a finished piece with trainer feedback.
Model, API, Cost & Build-vs-Buy Decision Record
Plan, produce, test and present a finished piece with trainer feedback.
AI Evaluation, Analytics & Risk Scorecard
Plan, produce, test and present a finished piece with trainer feedback.
AI Product Launch & Portfolio Capstone
Plan, produce, test and present a finished piece with trainer feedback.
TAKE THE NEXT STEP
Need fees, syllabus or the right batch?
An AI5 Academy advisor can help you compare mode, schedule and starting level.
TOOLS COVERED
ChatGPTClaudeGeminiPerplexityFigma AILovableOpenAI APILangChainVector DBMCPAnalytics
Tool coverage may be updated when the industry changes. Core methods remain part of the course.COMMON QUESTIONS
Before you apply
Why is this now a 12-week program?
Subject review showed that 8 weeks is too compressed for serious AI Product Management. The 12-week format gives proper time for discovery, PRD writing, prototyping, RAG, agents, model decisions, evaluation, launch planning and a portfolio case.
＋How much live training is included?
The professional program runs for 12 weeks with 36 live sessions: three sessions per week, 60–90 minutes each, approximately 36–54 instructor-led hours. Assignments and capstone work are additional.
＋Is coding required?
No for the core product work. Technical learners may connect prototypes to APIs as an added exercise.
＋Does it cover RAG and agents?
Yes. Learners cover RAG product planning, agentic AI, MCP, tool use, limitations and product controls from a PM viewpoint.
＋Does it cover AI evaluation and cost?
Yes. Task quality, human review, latency, cost, model choice, analytics, risk and product economics are included.
＋Can founders join?
Yes. The final case can be based on a new product or an AI feature for an existing service.
＋Do I need coding experience?
No, unless the course level says otherwise. Your advisor will check the right starting level.
＋Are classes live or recorded?
Classes are trainer-led in the classroom or live online.Recordings may support revision but do not replace class.
＋Will I receive a certificate?
Yes. Course completion requires attendance, assignments and the final project.
＋Can working professionals join?
Yes. Weekday, weekend and selected fast-track schedules are available.
＋NEXT BATCH
Choose your course.
Choose your schedule.
Online or offline. Weekdays or weekends. Regular or fast track. Speak with an AI5 Academy advisor about the right starting level.
COURSE PLANNING
AI Product Management Professional Program Course: syllabus, projects and admission details
Build AI product strategy, discovery, PRDs, prototypes, RAG and agent workflows, evaluation plans, launch systems and a career-ready capstone.
AI Product Management Professional Program Course syllabus
Week 1 — Product Management foundations for AI products, Week 2 — AI opportunity discovery and feasibility, Week 3 — User research, personas and JTBD. Read the full curriculum above for the complete learning sequence.
AI Product Management Professional Program Course projects
AI Product Foundations & Role Map; AI Opportunity & Feasibility Study; User Research, Persona & JTBD Pack. Check the project section for the work expected in this program.
AI Product Management Professional Program Course eligibility
Entry level: Intermediate. Ask a counsellor to confirm whether your background meets the program prerequisites.
AI Product Management Professional Program Course duration
Program duration: 12 weeks. Confirm the next batch timetable before joining.
AI Product Management Professional Program Course tools
ChatGPT, Claude, Gemini, Perplexity, Figma AI, Lovable. Tool access and any paid accounts should be confirmed for your cohort.
AI Product Management Professional Program Course fees and batches
Training mode: Online + Offline. Request current fees, available batches and a suitable schedule.
Get course details →