LIVE AI Product Manager Bootcamp: Scope, Orchestrate & Ship
Built Exclusively for Working Product & Project Managers
A live cohort-based AI Product Manager program designed to help you go from traditional PM workflows to building AI-first products covering LLM applications, AI product strategy, prompt engineering, prototyping, user research, and product execution. Learn from industry practitioners through hands-on sessions, real-world projects, and a capstone AI product build. Limited seats available.
The Cohort begins on 6th June, 2026 with live sessions on Weekends between 6 PM IST - 9 PM IST.
9
Weekends
19
Live Sessions
3
Live Stimulations
1
Capstone Project
1 Year
Access to Class Recordings
78+
Enrolled Learners
Join our Bootcamp
Learn In-demand Skills
Get Hired by Top Companies
9
Weekends
19
Live Sessions
3
Live Stimulations
1
Capstone Project
1 Year
Access to Class Recordings
78+
Enrolled Learners
Our Promise: in 9 weeks, this is who you become
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100% LIVE, instructor-led sessions every weekend with real-time interaction, Q&A, and doubt clearing.
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Covers a broad curriculum: LLM fundamentals and RAG pipelines to agents, MCP, evals, unit economics, and GTM strategy.
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Designed & taught by practitioners with hands-on experience building and shipping AI products.
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Get hands-on experience with the modern AI Product Manager tool stack
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Structured around judgment: when to use AI, when not to, and how to validate decisions using frameworks.
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Dedicated session on AI evals.
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Responsible AI built into the curriculum with hallucination handling, fallback design, failure modes, and EU AI Act basics.
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Capstone project reviewed by mentors.
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Demo Day in front of mentors and peers. Present your product, get feedback, and build a story you can speak to in interviews.
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Career support included - resume guidance, LinkedIn optimisation, and interview preparation to help you put your best foot forward.
Overview
What you'll learn in
this Live AI Product Manager Bootcamp
Week-1: PM Fundamentals + AI Fundamentals
PM & AI
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Session 1 - AI PM Intro & The AI Landscape
Evolution of the PM role in the AI age · Types of AI products & features · Traditional PM vs AI PM · Analytics vs Automation vs AI · AtliQ project examples
Output: Output: AI Product Landscape Map
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Session 2 - AI Family Tree + LLM Fundamentals
The AI family tree · AI Cheat Sheet for PM decisions · LLM fundamentals: transformers, tokens, context windows · Pre-training vs fine-tuning vs RAG vs prompting · Model selection across Claude, GPT-4o, Gemini, Llama · Token, embedding & inference cost
Output: Output: AI Decision Matrix + Model Selection Cheat Sheet
Week-2: AI Fundamentals
AI
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Session 3 - Prompting, RAG, Memory & Context Engineering
Prompting techniques · Context vs Behaviour Matrix · RAG pipeline end-to-end · Memory strategy · Prompt versioning in production · Failure modes: injection, jailbreaks, context overflow
Output: Output: Prompt Pack + RAG Context Flow Diagram
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Session 4 - Agents, Multi-Agent Workflows, MCP & OpenClaw
Agents vs chatbots vs assistants · Agent architecture: Sense, Plan, Act · Multi-agent workflows · Model Context Protocol (MCP) · Human-in-the-loop design · Autonomy staircase
Output: Output: Agent Workflow Blueprint + Autonomy Staircase Map
Week-3: PM Fundamentals
PM
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Session 5 - Problem Discovery & User Research
Why most products fail · Mom's Test & JTBD interviews · AI-shaped vs logic-shaped problems · Personas, empathy maps, 5-Why
Output: Output: Problem Discovery Brief + Interview Notes
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Session 6 - AI Design Thinking + AI Opportunity Mapping
AI Design Thinking loop · AI-shaped vs logic-shaped problems · 5-A Framework for use-case validation · Opportunity scoring matrix · The AI Opportunity Statement
Output: Output: JTBD Canvas + 5-A AI Use-Case Validation Sheet
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Session 7 - PRDs for AI Products + North Star Metrics + JTBD
AI PRD anatomy · Context pipeline in a PRD · Memory strategy · Failure modes & guardrails · North Star Metric for AI · Output vs outcome vs trust signals
Output: Output: AI PRD v1 + North Star Metric Sheet
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Session 8 - Stakeholder Management
Stakeholder management (Hem's live lecture) · Responsible AI: bias, fairness, transparency, hallucinations · EU AI Act overview for 2026
Output: Output: Stakeholder Map + Responsible AI Risk Checklist
Week-4: AI PM Foundations
AI PM
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Session 9 - AI Opportunity Mapping
5-A Framework for opportunity validation · Opportunity scoring matrix · Workflow mapping for AI interventions · AI vs non-AI solution framing
Output: Output: AI Opportunity Scoring Matrix + Opportunity Statement
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Session 10 - Designing AI Systems + Data Strategy
AI system design for PMs · Context pipeline & feedback loops · Data strategy & readiness · Privacy & compliance by design
Output: Output: AI System Map + Data Strategy Canvas
Week-5: AI PM Foundations
AI PM
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Session 11 - AI Roadmap + AI UX, Trust & Safety
AI roadmapping with model-dependent milestones · Now / Next / Later roadmap · AI UX principles · 3P Framework: Prioritisation, Placement, Prominence · Trust scaffolding & safety design
Output: Output: AI Roadmap + Trust & Safety UX Flow
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Session 12 - AI Evals: LLM vs Traditional + Metrics
Why traditional QA breaks for AI · LLM evals vs traditional evals · Golden datasets & error taxonomy · Offline vs online evals · LLM-as-a-Judge & LangFuse
Output: Output: AI Evaluation Plan + Metrics Scorecard
Week-6: AI PM Foundations
AI PM
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Session 13 - Context vs Behaviour Matrix + MVP with AI Tools
Context vs Behaviour Matrix for agents · MVP philosophy for AI products · No-code AI build with Lovable, v0, Bolt.new, n8n
Output: Output: Working AI MVP + Context vs Behavior Matrix
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Session 14 - AI Metrics, Pricing & Unit Economics
AI-specific metrics: activation, adoption, retention · Quality metrics: accuracy, precision, recall, F1 · Unit economics: CAC, LTV, gross margin · 3 AI pricing models: usage, seat, outcome · Freemium, tiered, credit-based pricing
Output: Output: AI Metrics Dashboard + Pricing & Unit Economics Sheet
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Session 15 - AI Product Strategy, Moats & GTM
AI-native vs AI-enabled strategy · Build vs buy vs partner · AI moats: data, workflow, feedback-loop, integration, distribution · GTM models: PLG, sales-led, enterprise · Pilot-to-paid conversion · Enterprise readiness
Output: Output: AI Product Strategy + Moat + GTM Canvas
Week-7: Build & Showcase
Capstone
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Session 16 - Capstone Introduction + LinkedIn Masterclass
Capstone scope & MVP boundary · Demo storyline & portfolio case study · LinkedIn headline, About, Featured project · What recruiters look for in AI PM profiles
Output: Output: Capstone Plan + LinkedIn Profile Brief
Week-8: Build & Showcase
Capstone
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Session 17 - Capstone Review + Portfolio Structuring
First capstone draft review · PRD completeness check · UX trust & fallback flows · Eval plan & roadmap review · Mentor & peer feedback scorecard
Output: Output: Capstone Plan + MVP Scope + LinkedIn Pack
Week-9: Career Readiness & Demo Day
Capstone
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Session 18 - Career Readiness + Capstone Polish + Final Mock & Demo Rehearsal
AI PM resume bullets · LinkedIn positioning refinement · Product sense & AI case interview practice · Mock interviews · 5-minute demo rehearsal · Final portfolio readiness
Output: Output: Demo-Ready Portfolio + Mock Interview Pack
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Session 19 - Demo Day
Final AI PM product showcase · Prototype walkthrough · Evaluation & metrics overview · Pricing & GTM overview · Mentor and judge Q&A · Public LinkedIn portfolio publish
Output: Output: Final AI PM Portfolio + Demo Presentation + Publishing Plan
Learn From
The People Who Build and Ship AI Products
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Dhaval Patel
Founder, Codebasics · Ex-NVIDIA
Curriculum advisor. Sets what this cohort teaches and what it refuses to.
I have 17 years of experience in programming and data science working for big tech companies like NVIDIA and Bloomberg. I also run a famous youtube channel called Codebasics where I pursue my passion for teaching. Codebasics is one of the top channels on youtube when it comes to data science, machine learning, data structures, etc. I firmly believe that “Anyone can code” and I use analogies, simple explanations, and step-by-step storytelling to explain difficult concepts in such a way that even a high school student can understand them easily.
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Hemanand Vadivel
CEO, Codebasics
Leads most sessions and every leadership and management block.
I’m a mechanical engineer who transitioned to a full time Data & Analytics manager in the UK & Germany by teaching myself Power BI, excel & anything else that was required to solve the problem. I have worked with complex data across Supply Chain, Sales, Marketing, Revenue Management, Finance and HR functions over the last 8 years to deliver effective solutions. To me, Analytics is an extra sensory organ that anyone can develop to become a superhuman at work. I have conducted several workshops and internal training to help non-technical people to become superhuman at work and now, really excited for this opportunity to share all that knowledge with you.
Hear It From
Our Happy Learners
Our content is rated 4.9/5 from 1344+ Learners
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Director of Product Management
LIVE AI Product Manager: Batch 1
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I joined the Codebasics AI Product Management cohort because I wanted something practical, not a regular PM course with AI added on top.
What stood out for me is how AI is built into the whole product journey, from discovery and AI opportunity mapping to metrics, evals, cost, guardrails and GTM. The instructors are industry practitioners and that keeps the learning grounded in how products are actually built.
The breakout sessions were equally valuable. Working through real problems with professionals from diverse domains brought different perspectives and made the learning much more practical.
One idea that really stayed with me is simple. Start with the problem, not the AI. Understand the workflow and pain points first then use AI opportunity mapping to decide where AI genuinely adds value.
The capstone brings everything together. It is not just about building an AI app but about working through the full AI product journey, from problem discovery and product definition to cost, metrics, evals, guardrails, a working prototype and stakeholder presentation.
Overall, it has been a practical and highly structured way to learn how to think like an AI product manager, not just how to build with AI.
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One of the best-designed and best-delivered AI Product Management courses I have attended so far. Hats off to the entire team for the thought, planning, and effort that has gone into designing this learning journey.
This is truly "AI Product Management in Practice," not just another theory-based course. I genuinely feel that if I hadn't taken this course, I wouldn't even have known that many of these topics existed. Several of them are rarely discussed in books, yet they become incredibly important when you're working on AI products. This course brought those hidden but essential concepts into the open.
Each mentor brings a unique perspective, and together they make the course incredibly comprehensive. Thanks to all mentors and the team who made this course possible.
I am truly grateful to have had the opportunity to be part of this course. In a way, I had manifested finding a course exactly like this—and I'm so glad it became a reality.
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The AI Product Management course by Codebasics has been a fantastic learning experience. A special thanks to Dhaval, Akshay, Karandeep, Aakash, and Mochitha for making the sessions practical, engaging, and easy to understand.
What I really appreciated was the focus on real-world AI product management rather than just theory. The sessions covered everything from identifying AI opportunities and creating PRDs to AI capabilities, evaluation frameworks, guardrails, success metrics, MVP scoping, GTM, AI moats, and roadmaps.
The instructors brought different perspectives and explained concepts through practical examples and industry use cases, which made it much easier to understand how AI products are actually built and taken from an idea to implementation.
Overall, this course has significantly strengthened my understanding of AI Product Management and the end-to-end AI product lifecycle. I would definitely recommend the course to anyone looking to build or transition into a career in AI Product Management.
Thank you to the entire Codebasics team and all the instructors for putting together such a valuable and practical learning experience!
I was part of the pilot batch of the Codebasics AI Product Manager program, and it was one of the best online learning experiences I’ve had. I’ve taken courses from well-known universities, and the teaching here wasn’t merely comparable—it was better.
The program gets the technical depth exactly right. It doesn’t turn product managers into engineers, but it gives them enough understanding to make informed decisions and have credible conversations with technical teams. Having also completed the Codebasics AI Engineering Bootcamp, I could clearly see how thoughtfully the two programs draw that boundary.
What stood out most was how much Dhaval, Akshay, Karan, Hem, and the entire team cared about whether we genuinely understood the material. Every concept was made practical: building agents in different ways, evaluating costs, turning an idea into a defensible business case, and adapting the conversation for an AI engineer, CIO, or business stakeholder. The role-plays were especially valuable.
When a topic moved too quickly, the team listened and arranged an additional session. That responsiveness, combined with their openness, curiosity, and respect for the cohort’s experience, made the classes feel like genuine conversations.
I finished the program with skills I could apply at work immediately. I highly recommend it to aspiring AI product managers, business analysts, project managers, and functional consultants who want practical AI literacy and the confidence to lead AI initiatives.
Abhishek Timmaraju
Senior Director IT Operations & Enterprise Applications
LIVE AI Product Manager: Batch 1
I enrolled in the AI PM Bootcamp expecting to learn general AI PM frameworks and terminology. What I actually walked away with was something more specific - a real mindset change in how I approach implementing AI in product problems, which is a different layer than regular PM work. The capstone project was the turning point. Instead of a hypothetical case study, I worked on a real business problem, which meant I had to make actual tradeoffs, not just theoretical ones. It also taught me where AI actually belongs in a product and where it doesn't - not every problem needs an AI solution, and knowing which is which matters more than the AI itself.
The rest of it felt different too, mainly because it came from founders who've actually built and shipped AI products themselves. They weren't teaching from a textbook; they were sharing what they'd learned the hard way, mistakes included. That made me take every exercise more seriously - this wasn't theory, it was real lessons from people who'd actually been in the room when things worked and when they didn't. I came out of this bootcamp thinking like an AI product manager, not just knowing what one does.
The Codebasics Promise
Build & Ship Production AI in 9 Weeks.
Not theory. A working cohort where you build real AI products.
| What you get | Self-study | Other live bootcamps | Our live cohort |
|---|---|---|---|
| Live, mentor-led sessions | |||
| Real AI work you ship | Rarely | Sometimes | A real client project |
| The current 2026 AI product stack | On your own | Often dated | |
| Job assistance | |||
| Investment | Your time | Usually far higher | US$840 |
May we help you?
Frequently Asked
Questions
Q.1
How is this live bootcamp different from other bootcamps?
Q.2
When does this begin and when are the live sessions held?
Sessions are held on Saturdays and Sundays, 6 PM to 9 PM IST. Three hours per session, two sessions per week.
Q.3
What happens after 9 weeks?
Q.4
What if I miss a live session?
Q.5
What is the Soft Skills Bootcamp and how do I access it?
Once you enroll in the Cohort, access is included automatically. Log into your Codebasics dashboard, go to your AI PM Cohort section, and you will find the Soft Skills Bootcamp courses listed there alongside your cohort materials. No separate purchase or enrollment needed.
Q.1
Is this designed for fresh graduates?
Q.2
Do I need coding experience?
Q.1
Do you offer job placement?
Q.1
I already purchased the Soft Skills Bootcamp or a course that is part of it. Do I get a price reduction on the AI PM Cohort?
Q.1
What is the refund policy?
Q.1
When do registrations close?
Q.2
Can I join after the sessions are started?
Q.1
Do I need to pay for the no-code tools used in the capstone - Lovable, v0, Bolt.new, n8n?
If you later want to scale your product significantly beyond what the free tiers allow, paid plans are available on each platform, but that decision is entirely yours after the cohort ends, and it is not a requirement.
Q.1
How is this live bootcamp different from other bootcamps?
Q.2
When does this begin and when are the live sessions held?
Sessions are held on Saturdays and Sundays, 6 PM to 9 PM IST. Three hours per session, two sessions per week.
Q.3
What happens after 9 weeks?
Q.4
What if I miss a live session?
Q.5
What is the Soft Skills Bootcamp and how do I access it?
Once you enroll in the Cohort, access is included automatically. Log into your Codebasics dashboard, go to your AI PM Cohort section, and you will find the Soft Skills Bootcamp courses listed there alongside your cohort materials. No separate purchase or enrollment needed.
Q.1
Is this designed for fresh graduates?
Q.2
Do I need coding experience?
Q.1
Do you offer job placement?
Q.1
I already purchased the Soft Skills Bootcamp or a course that is part of it. Do I get a price reduction on the AI PM Cohort?
Q.1
What is the refund policy?
Q.1
When do registrations close?
Q.2
Can I join after the sessions are started?
Q.1
Do I need to pay for the no-code tools used in the capstone - Lovable, v0, Bolt.new, n8n?
If you later want to scale your product significantly beyond what the free tiers allow, paid plans are available on each platform, but that decision is entirely yours after the cohort ends, and it is not a requirement.
Become an AI-native PM in 9 weeks.
