LIVE AI Product Manager Bootcamp: Scope, Orchestrate & Ship
Built for Working Professionals Transitioning into AI Product Management
18
Live Sessions
9
Weeks
Live
Client & Expert Interactions
1
AI Product Shipped
1 Year
Access to Class Recordings
82+
Enrolled Learners
18
Live Sessions
9
Weeks
Live
Client & Expert Interactions
1
AI Product Shipped
1 Year
Access to Class Recordings
82+
Enrolled Learners
Our Promise: in 9 weeks, this is who you become
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100% live, instructor-led weekend sessions with real-time interaction, Q&A, and doubt clearing.
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Learn from experienced AI product professionals, AI engineers, and data scientists from AtliQ Technologies and other companies, with exposure to real business challenges and practical AI use cases.
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A comprehensive AI Product Management curriculum, covering LLM fundamentals, RAG pipelines, AI agents, AI evals, unit economics, pricing, and go-to-market strategy.
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Designed and taught by industry practitioners with hands-on experience building and shipping AI products.
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Hands-on experience with the modern AI Product Manager tool stack through practical exercises, prototypes, and project work.
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Built around product judgment, helping you understand when to use AI, when not to, and how to validate decisions using practical frameworks.
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Dedicated coverage of AI evaluations, including quality measurement, testing approaches, and success metrics.
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Responsible AI integrated into the curriculum, covering hallucination handling, failure-mode mapping, guardrails, and the basics of the EU AI Act.
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A mentor-reviewed capstone project that helps you take an AI product from problem discovery to prototype and stakeholder presentation.
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Demo Day with mentors and peers, where top capstone projects are presented for feedback, and every student builds a compelling project story for interviews.
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Career support included, with resume guidance, LinkedIn optimisation, and live mock interview practice to help you put your best foot forward.
Overview
What you'll learn in
this Live AI Product Manager Bootcamp
Week-1: AI PM Fundamentals + AI Foundations
PM & AI
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Session 1 - The AI Product Manager
Why AI is changing Product Management · AI PM salaries & hiring trends · Types of AI PMs · AI PM vs PM vs TPM vs ML PM · Traditional PM vs AI PM · Scope & responsibilities · AI-first thinking · Future of Product Management
Output: AI PM Role Map + Program Roadmap
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Session 2 - AI Foundations for Product Managers
The AI Family Tree · AI vs ML vs Deep Learning vs Generative AI · Rule-based Systems vs ML vs GenAI vs AI Agents · Supervised, Unsupervised & Reinforcement Learning · Classification vs Regression vs Clustering · LLM Fundamentals · Tokens · Embeddings · Semantic Search · Vector Databases · RAG · Hallucinations
Output: AI/ML Landscape Map + LLM Cheat Sheet
Week-2: Problem Discovery + Evaluation & Guardrails
AI PM
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Session 3 - AI Problem Discovery & User Research
Why AI projects fail · AI Discovery Framework · JTBD · Mom Test · Personas · Empathy Mapping · 5 Whys · Live examples and use cases (Dr Sara and HR)
Output: Discovery Framework + Persona Canvas
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Session 4 - AI Evaluation & Guardrails
AI Eval Stack: human eval vs LLM-as-a-Judge · Precision, Recall, F1, AUC-ROC · LangSmith / Ragas (intro) · Guardrails & why PMs need them · Hallucination Mitigation · Safety Guardrails
Output: Eval Scorecard + Guardrail Checklist
Week-3: Product Metrics & Analytics + AI PRDs
AI PM
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Session 5 - AI Metrics, Product Analytics & Experimentation
AI Metrics · Product Metrics · Business Metrics · North Star Metric · AARRR · A/B Testing
Output: Metrics Framework + A/B Test Plan
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Session 6 - AI PRDs & Designing AI Products
Product Development Lifecycle · BRD vs PRD vs FRD · AI PRD - live build with the class
Output: AI PRD Template
Week-4: Prompting & RAG + AI Toolkit & Vibe Coding
AI
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Session 7 - Prompting, Context & RAG for AI PMs
RCTF Framework · Zero/one/few-shot prompting · Context Engineering: PM vs engineering control · Structured Outputs · What/why/how of RAG · Fine-tuning vs Prompting vs RAG · Prompt Versioning
Output: Prompt Pack + RAG Decision Guide
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Session 8 - AI PM Toolkit & Vibe Coding (Building a RAG Application)
Tools: ChatGPT, Claude, Gemini, Perplexity, NotebookLM, Claude Code, Claude Design, Git/Github · Building MVPs without coding · Live RAG chatbot build (telecom example) · Tech stack: Groq, IDE
Output: AI Tool Stack Map + Live RAG Chatbot Build
Week-5: AI Agents & Automation + Stakeholder Management
AI PM
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Session 9 - AI Agents, MCP & Automation
AI Agents & their types · Tool Calling · MCP · Memory · Multi-Agent Systems · Zapier / n8n / Make · LangChain intro · LangChain VibeCoding Project · AI Workflow Automation | Modal
Output: Agent Workflow Blueprint + Automation Map
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Session 10 - Stakeholder Management + Capstone
Communication as a timeless PM skill · The AER Framework · Listening ratio & self-awareness · Stakeholder mapping & power-interest grid · Capstone project launch
Output: Stakeholder Map + Capstone Brief
Week-6: AI System Design + Data Strategy
AI PM
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Session 11 - AI and Data Strategy (System Design) - 1
GPT vs Claude vs Gemini vs Open Source · Reading Model Benchmarks · Cost vs Quality vs Latency · Multimodal AI · Build vs Buy vs Partner · MVP definition · Automation vs ML vs GenAI vs Agent Decision Framework · AtliQ case studies
Output: Model Selection Matrix + System Design Canvas
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Session 12 - AI and Data Strategy (System Design) - 2
Why data strategy matters · PM vs data engineer responsibilities · Types of context · Data procurement & readiness · Golden data & storage · MLOps (PM Perspective)
Output: Data Readiness Checklist + MLOps Overview
Week-7: Responsible AI & UX + AI Economics
AI PM
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Session 13 - Responsible AI, AI Ethics & UI UX Design
Responsible AI · Bias & Fairness · Privacy · Security · Governance · AI Compliance (EU AI Act) · AI UX Principles & HAX Toolkit
Output: Responsible AI Checklist + UX Principles Card
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Session 14 - AI Economics & Business Models
Token Economics · Model Pricing · Cost Optimization · Usage-based Pricing · Unit Economics (RAG chatbot cost activity) · ROI
Output: Cost Estimation Model + ROI Calculator
Week-8: GTM & AI Moats + Opportunity Mapping
AI PM
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Session 15 - GTM, AI Moats & Scaling AI Products & Feasibility Impact Analysis
Go-to-Market Strategy · AI Adoption · Change Management · AI Pricing Strategy · SWOT · TAM/SAM/SOM · AI Flywheel · AI Moats · AI Roadmaps
Output: GTM Canvas + AI Roadmap Template
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Session 16 - AI Opportunity Mapping
The Miro Process Board · 33A AI Cards · Workflow Mapping for AI Use Cases · Guardrails & Human-in-the-Loop placement
Output: Opportunity Map + Guardrail Placement
Week-9: Career Readiness + Personal Branding
Career
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Session 17 - AI PM Career Readiness & Mock Interviews
Resume Review · LinkedIn Optimization · Portfolio/GitHub Review · Mock Interview Process · Live Mock Interviews · Interview Feedback & Best Practices · AI Product Operating Rhythm
Output: ATS Resume + LinkedIn Checklist + Live Mock Interview + Feedback Report
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Session 18 - LinkedIn Personal Branding Workshop
How to build your personal brand on LinkedIn · LinkedIn Profile Optimization
Output: Personal Brand 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 1349+ 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, 5 PM to 8 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, 5 PM to 8 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.
Begin Your Journey
