AI5 PROFESSIONAL CERTIFICATE · BY TGC INDIA · UPDATED AUGUST 2026
AI Product Management
Research, specify, prototype, evaluate and launch AI products using modern AI PM workflows.
Online + OfflineWeekdays + WeekendsRegular + Fast Track
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.
Learn to take an AI product from user problem and AI PRD through prototyping, RAG and agent feasibility, model and API decisions, evaluation, economics, launch 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 and model decision skills
You want RAG, agent, evaluation, launch and career portfolio practice
YOUR LEARNING ARC
From guided foundation to finished work.
Frame
Find the user problem, product boundary and AI feasibility.
Specify
Write AI PRDs with data, model, workflow and acceptance checks.
Prototype
Create AI UX, RAG and agent product prototypes.
Measure
Plan evaluation, economics, launch and career-ready product evidence.
INDUSTRY TASKS
Practise the work, not only the tool.
- AI Opportunity & Feasibility Study
- AI PRD
- AI UX Prototype
- RAG Product Prototype
- Agentic AI/MCP Product Prototype
- AI Product Launch & Career 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 and feasibility study.
02
Write testable AI product requirements
An AI PRD covering users, data, model, workflow and acceptance checks.
03
Prototype AI, RAG and agentic product experiences
AI UX, RAG and Agentic AI/MCP prototypes with failure and correction paths.
04
Choose models and measure product quality
A model decision record, evaluation system and economics view.
05
Plan launch and career presentation
A launch-ready 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
8 learning modules
Research, specify, prototype, evaluate and launch AI products with strong AI-PM foundations, RAG and agent awareness, model/API decision skills and a career-ready portfolio.
AI-PM foundations and opportunity framing
Separate real customer problems from attractive but weak AI ideas.
CORE TOPICS
- AI product types, LLM capability and limits
- User problem, job and workflow definition
- Opportunity, feasibility and risk scoring
- Success measures and product boundaries
GUIDED PRACTICE
Assess several product ideas and prepare a clear feasibility case for one.
MODULE DELIVERABLE
AI Opportunity & Feasibility Study
AI user research and product discovery
Use AI to speed research while keeping evidence, source checks and human judgement visible.
CORE TOPICS
- Interview, survey and desk-research plans
- AI-assisted synthesis and assumption logs
- Competitor and user journey analysis
- Problem statements and product hypotheses
GUIDED PRACTICE
Conduct or simulate discovery and turn findings into a product direction.
MODULE DELIVERABLE
AI Product Discovery Pack
AI PRD and product specification
Turn discovery into requirements that design, engineering and business teams can test.
CORE TOPICS
- AI PRD structure and acceptance checks
- Data, model and workflow requirements
- User stories, edge cases and constraints
- Human-in-the-loop and approval paths
GUIDED PRACTICE
Write a complete AI PRD for one feature or product workflow.
MODULE DELIVERABLE
AI PRD
AI UX, conversation and prototyping
Design how users direct, inspect, correct and trust an AI feature.
CORE TOPICS
- Prompt and interaction patterns
- Trust, citations, uncertainty and refusals
- Error, correction and recovery states
- Figma AI, Lovable and rapid prototype workflows
GUIDED PRACTICE
Create and test an AI product prototype covering normal and failure paths.
MODULE DELIVERABLE
AI UX Prototype
RAG product planning
Plan products that answer from approved knowledge rather than unsupported model memory.
CORE TOPICS
- RAG use cases and knowledge boundaries
- Documents, chunking, embeddings and vector search
- Citations, freshness and permission checks
- Build, buy and maintenance decisions
GUIDED PRACTICE
Design and prototype a knowledge-backed product experience.
MODULE DELIVERABLE
RAG Product Prototype
Agentic AI, MCP and workflow products
Understand when an AI product should use tools, actions, memory and connected systems.
CORE TOPICS
- Agent workflows and task boundaries
- Tool calling, MCP and approval design
- Multi-step automation and escalation
- Failure, misuse and safety cases
GUIDED PRACTICE
Map an agentic product workflow with permissions, fallbacks and tests.
MODULE DELIVERABLE
Agentic AI/MCP Product Prototype
Model, API, evaluation and economics
Choose models and APIs using quality, speed, cost, reliability and risk trade-offs.
CORE TOPICS
- Model and vendor selection criteria
- Prompting, APIs and structured outputs
- LLM evaluation, human review and analytics
- Latency, token cost, ROI and operating economics
GUIDED PRACTICE
Create an evaluation plan and model decision record for the prototype.
MODULE DELIVERABLE
AI Evaluation System
Launch, roadmap and career capstone
Prepare a controlled release and package the work as credible AI PM portfolio evidence.
CORE TOPICS
- MVP scope and prioritisation
- GTM, adoption and stakeholder communication
- Post-launch feedback, incidents and iteration
- Portfolio case study, interview story and career positioning
GUIDED PRACTICE
Present the product from user problem through PRD, prototype, tests, economics and launch plan.
MODULE DELIVERABLE
AI Product Launch & Career Capstone
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 Opportunity & Feasibility Study
Plan, produce, test and present a finished piece with trainer feedback.
AI PRD
Plan, produce, test and present a finished piece with trainer feedback.
AI UX Prototype
Plan, produce, test and present a finished piece with trainer feedback.
RAG Product Prototype
Plan, produce, test and present a finished piece with trainer feedback.
Agentic AI/MCP Product Prototype
Plan, produce, test and present a finished piece with trainer feedback.
AI Product Launch & Career 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
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 and product behaviour 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.