Become an AI Project Manager

A live, hands-on program that takes you from PMBOK 7 (Project Management Body of Knowledge, 7th Edition) and Agile fundamentals to running real AI projects — data pipelines, MLOps, AI agents, governance and vendor economics — and prepares you for the CPMAI certification. Beginner courses in AI, cloud and AWS are included free, so you can start from zero.

Beginner courses included 10 modules · 105+ lessons 28 practical exercises · 7 labs 3 portfolio projects 9 knowledge checks + 4 CPMAI mock tests
46,000+professionals trained
10modules · 105+ lessons
3portfolio projects
4.6/5 on Trustpilot · 267+ reviews
Verified reviews

What K21 Academy learners say

4.6 Trustpilot & Google
Rated 4.6/5 from 267 reviews on Trustpilot
Layer 1 — Common Foundation for Everyone

Start from zero.
Seven foundation courses, included.

You do not need a cloud background, an AI background or any coding to join. These seven self-paced courses come free with your enrollment and open the moment you enrol — work through them before the live cohort starts and you will arrive on day one already fluent in the vocabulary.

For Everyone

AI, ML & GenAI for Beginners

What is AI, Machine Learning, Deep Learning, GenAI and LLMs — and 10+ more core concepts.

Modules Covered

  • What is AI, Machine Learning, and Deep Learning?
  • Generative AI and Large Language Models explained simply
  • Supervised vs unsupervised vs reinforcement learning
  • Real-world AI/ML use cases across industries
  • Introduction to foundation models: Claude, Titan, Llama
  • How models learn: training, inference, and evaluation
  • AI safety and responsible AI basics
  • ⚡ Lab: Explore a foundation model in a playground
  • ⚡ Lab: Build your first simple AI chatbot
For Everyone

Cloud for Beginners

What cloud computing is and why it matters — AWS, Azure, Google and Oracle concepts, and 8 more core concepts.

Modules Covered

  • What is cloud computing and why it matters
  • Public vs private vs hybrid cloud
  • IaaS, PaaS, SaaS — what each is good for
  • Overview of AWS, Google Cloud, Oracle Cloud and Azure
  • Core cloud concepts: regions, availability zones, scalability
  • Cloud pricing models and cost basics
  • Cloud security fundamentals
  • ⚡ Lab: Explore free tiers across cloud providers
For Everyone

AWS for Beginners

Core AWS services, pricing, free tier and billing setup — EC2, S3, RDS, IAM, VPC and 8+ core concepts.

Modules Covered

  • What is cloud computing and why AWS
  • EC2: instance types, AMIs, pricing models
  • S3: buckets, storage classes, lifecycle
  • RDS managed databases: MySQL, PostgreSQL, Aurora basics
  • IAM: users, groups, roles and permission policies
  • VPC: virtual private cloud, subnets, security groups
  • AWS Pricing Calculator & Cost Explorer overview
  • ⚡ Lab: Create an AWS free tier account
  • ⚡ Lab: Set up billing alerts & budget controls
For Everyone

Azure for Beginners

Azure portal, subscriptions and resource groups — and 11 more core concepts.

Modules Covered

  • Azure portal, subscriptions and resource groups
  • Core Azure services: compute, storage, networking
  • Azure Active Directory and identity basics
  • Setting up your first Azure environment
  • Azure governance: policies, blueprints, management groups
  • ⚡ Lab: Register an Azure free trial account
  • ⚡ Lab: Create budget & billing alerts
  • ⚡ Lab: Create a Windows VM (quick start)
  • ⚡ Lab: Troubleshooting — connect to a VM on cloud
  • ⚡ Lab: Open an Azure support request
  • ⚡ Lab: Requesting Azure service quota increases
  • ⚡ Lab: Billing Q&A
For Everyone

Google Cloud for Beginners

Google Cloud projects, billing and core services — Compute Engine, Cloud Storage, BigQuery, IAM, VPC and 8+ core concepts.

Modules Covered

  • What is Google Cloud and how it compares to AWS and Azure
  • Projects, folders, organizations and billing accounts
  • Compute Engine: machine types, images and pricing models
  • Cloud Storage: buckets, storage classes and lifecycle rules
  • Databases and analytics: Cloud SQL and BigQuery basics
  • IAM: members, roles and policies
  • VPC networking, subnets and firewall rules
  • Google Cloud pricing calculator & billing reports
  • ⚡ Lab: Create a Google Cloud free tier account
  • ⚡ Lab: Set up a budget & billing alerts
  • ⚡ Lab: Launch your first Compute Engine VM
  • ⚡ Lab: Explore BigQuery with a public dataset
Exam Q&A

AI-900: Introduction to AI in Azure — Exam Q&A

Three full mock tests with answers, covering the Microsoft Azure AI Fundamentals syllabus.

Mock Tests Included

  • ☑ Mock Test 1 — full-length, with answers
  • ☑ Mock Test 2 — full-length, with answers
  • ☑ Mock Test 3 — full-length, with answers
Exam Q&A

AWS Certified AI Practitioner — Exam Q&A

Three full mock tests with answers, covering the AWS Certified AI Practitioner syllabus.

Mock Tests Included

  • ☑ Mock Test 1 — full-length, with answers
  • ☑ Mock Test 2 — full-length, with answers
  • ☑ Mock Test 3 — full-length, with answers
Your AI project management learning path

From PMBOK 7 foundations
to shipping real AI projects.

PMBOK 7 is the 7th edition of PMI's Project Management Body of Knowledge — the principle-based standard that replaced the old process-driven model and now covers predictive, Agile and hybrid delivery. Module 1 maps those principles onto the AI project lifecycle.

Ten modules in delivery order — foundations and Agile first, then the AI/ML and data knowledge a PM actually needs, then tools, risk, stakeholders and economics, finishing with a full project simulation and MLOps delivery. Every module ends with exercises and a knowledge check.

Foundations

Module 1 — PMBOK 7 + AI Project Management Foundations

Map what you already know about project management onto AI work — where PMBOK 7 still holds, where AI projects break the traditional playbook, and how to structure a POC, WBS and backlog.

13 lessons · 3 exercises · quiz

  • Overview & concepts
  • AI projects vs traditional projects
  • Mapping PMBOK 7 (Project Management Body of Knowledge, 7th Edition)
  • AI project adaptation & the AI project lifecycle
  • AI project lifecycle — real world example
  • AI project approaches
  • Real world AI project success or failure
  • Common mistakes in managing AI projects
  • Key takeaways & the PM mindset shift
  • WBS with an example project
  • POC (proof of concept)
  • Backlog overview
  • Backlog components & AI backlog structure
  • ✎ Exercise 1 — Traditional vs AI projects: case study comparison
  • ✎ Exercise 2 — Building an AI project charter
  • ✎ Exercise 3 — AI project planning & estimation
  • ☑ Knowledge check — Module 1 quiz
Agile Delivery

Module 2 — Agile, Scrum & Kanban for AI Teams

Why waterfall fails on AI work, and how Scrum, Kanban and dual-track Agile adapt when your sprint contains experiments that might not work.

13 lessons · 4 exercises · quiz

  • Overview & concepts
  • Scrum and roles in Scrum
  • The Kanban approach in project management
  • Scrum + Kanban = Scrumban
  • User stories & the INVEST framework in AI PM
  • Why waterfall fails AI projects
  • Traditional software Agile vs AI Agile
  • Dual-track Agile
  • Discovery track vs delivery track
  • Scrum roles in AI teams
  • Sprint planning for AI experiments
  • Managing AI experiments in an Agile framework
  • Making Agile work for AI teams
  • ✎ Exercise 1 — Sprint planning role-play: AI fraud detection project
  • ✎ Exercise 2 — Sprint review simulation: presenting negative results
  • ✎ Exercise 3 — Backlog organization
  • ✎ Exercise 4 — Kanban board design
  • ☑ Knowledge check — Module 2 quiz
Technical Fluency

Module 3 — Understanding AI/ML for Project Managers

Enough AI/ML depth to lead the room without being an engineer: model types, how models are built, which metrics matter, and where the real risks sit.

9 lessons · 3 exercises · quiz

  • Overview & concepts
  • Types of machine learning
  • AI use cases and business applications
  • How AI models are built
  • Types of metrics
  • AI risks PMs should know
  • The AI project checklist
  • Key points to remember
  • RAG (retrieval-augmented generation)
  • ✎ Exercise 1 — AI suitability assessment across 10 business problems
  • ✎ Exercise 2 — Confusion matrix & model evaluation
  • ✎ Exercise 3 — Data requirement document: sentiment analysis project
  • ☑ Knowledge check — Module 3 quiz
Data & Delivery

Module 4 — Data Lifecycle & AI Project Delivery

The biggest module in the program: estimation with real uncertainty, Monte Carlo forecasting, the full data lifecycle, MLOps, deployment strategies and the checkpoints a PM owns.

20 lessons · 4 exercises · quiz

  • Overview & concepts
  • Team-based estimation discussion
  • Monte Carlo simulation
  • User stories and the Fibonacci series
  • Scrubbing
  • Monte Carlo demo + tools
  • AI model workflow
  • Pretrained models
  • Data as the foundation
  • The data lifecycle in AI
  • Data pipelines and ETL
  • Data quality dimensions
  • Data dependencies in projects
  • MLOps & key practices
  • Deployment strategies
  • Strategy selection by the PM
  • SaaS
  • Monitoring essentials
  • PM checkpoints in data-heavy projects
  • Success factors for AI projects
  • ✎ Exercise 1 — Map a data pipeline: customer churn prediction
  • ✎ Exercise 2 — Review an experiment tracking log
  • ✎ Exercise 3 — Design a deployment pipeline
  • ✎ Exercise 4 — Design a monitoring dashboard: fraud detection model
  • ☑ Knowledge check — Module 4 quiz
Tools & Agents

Module 5 — AI Tools & Agents for Project Managers

The most hands-on module: build five working AI assistants for your own PM workflow — standup bot, risk analyzer, status report generator, capacity forecaster and a live project dashboard.

13 lessons · 5 labs · 2 exercises · quiz

  • Overview & concepts
  • Model governance
  • Guardrails
  • AI tools & intelligent agents
  • Prompt engineering
  • The AI tools ecosystem
  • What are AI agents
  • Status reports & risk analysis
  • Capacity planning
  • Benefits of AI agents
  • PM productivity comparison
  • Data analysis tools & the visualization ecosystem
  • Zapier + AI agent fundamentals
  • ⚡ Lab 1 — Daily Standup Summary Bot (building your first PM agent)
  • ⚡ Lab 2 — Project Risk Analyzer (advanced PM agents)
  • ⚡ Lab 3 — Weekly Status Report Generator (advanced PM agents)
  • ⚡ Lab 4 — Resource Capacity Forecaster (advanced PM agents)
  • ⚡ Lab 5 — Build an AI Project Dashboard (Power BI for AI project reporting)
  • ✎ Exercise 1 — Use AI for core PM tasks
  • ✎ Exercise 2 — Build an AI project dashboard
  • ☑ Knowledge check — Module 5 quiz
Risk & Governance

Module 6 — Risk, Governance & Responsible AI

Score and prioritize AI-specific risks, run a real risk register, and put responsible-AI practice into the delivery process instead of the policy document.

12 lessons · 2 exercises · quiz

  • Overview & concepts
  • AI project risks
  • Categories of AI risks
  • The AI risk assessment framework
  • Risk scoring & prioritization
  • Risk register structure & management types
  • AI governance principles
  • The compliance lifecycle flow
  • Real world AI failure examples
  • Responsible AI practices for PMs
  • Implementing responsible AI
  • Building trust through responsible AI
  • ✎ Exercise 1 — Create an AI risk register
  • ✎ Exercise 2 — Conduct a mock AI ethics review
  • ☑ Knowledge check — Module 6 quiz
Stakeholders

Module 7 — Stakeholder Communication & Change Management

Explain AI to non-technical leaders, report differently to executives and engineers, communicate bias and failure honestly, and run AI adoption with ADKAR.

11 lessons · 3 exercises · quiz

  • Overview & concepts
  • Why AI projects fail
  • Stakeholder types in AI
  • Stakeholder mapping and the RACI matrix
  • Explaining AI to non-technical leaders
  • AI experimentation
  • Executive vs technical reporting
  • Communicating risk, bias & failure
  • Change management for AI adoption & ADKAR
  • Types of resistance to AI adoption
  • Communication cadence & channels
  • ✎ Exercise 1 — Create an AI project status report
  • ✎ Exercise 2 — Roleplay stakeholder scenarios
  • ✎ Exercise 3 — Create a change management plan
  • ☑ Knowledge check — Module 7 quiz
Economics

Module 8 — AI Project Economics & Vendor Management

Where AI budgets actually go: cost components, total cost of ownership, cloud cost drivers, ROI you can defend, and build vs buy vs partner decisions.

9 lessons · 2 exercises · quiz

  • Overview & concepts
  • AI project architecture
  • Cost components in AI projects
  • TCO for AI & reduction strategies
  • Financial planning
  • ROI calculation
  • Cloud cost drivers
  • Build vs buy vs partner strategy
  • Evaluating AI vendors & SLA considerations
  • ✎ Exercise 1 — Create an AI project budget and ROI model
  • ✎ Exercise 2 — Vendor evaluation & selection
  • ☑ Knowledge check — Module 8 quiz
Simulation

Module 9 — Real AI Project Simulation & Portfolio

Run a full AI project end to end — risks, issues, dashboards, stakeholder comms — and walk out with portfolio artifacts you can show in an interview.

5 lessons · 4 simulation activities · quiz

  • Overview & concepts
  • Risk management & issue tracking
  • Monitoring dashboard & stakeholder communication
  • Portfolio artifacts & the AI project lifecycle
  • Dashboard mockups & timeline diagram
  • ✎ Simulation Activity 1 — Project initiation & planning
  • ✎ Simulation Activity 2 — Agile execution simulation
  • ✎ Simulation Activity 3 — Risk & crisis management
  • ✎ Simulation Activity 4 — Project portfolio & presentation
  • ☑ Knowledge check — Module 9 quiz
Advanced

Module 10 — AI Delivery Excellence & MLOps for PMs

The final module: what separates a delivered model from a delivered product — MLOps ownership, monitoring in production, and delivery excellence as an AI PM.

2 labs · 1 exercise

  • AI delivery excellence for project managers
  • MLOps ownership and handover
  • Production monitoring and model drift
  • Bringing every module together into one delivery model
  • ⚡ Lab 1 — Design a complete MLOps pipeline (deep dive into MLOps)
  • ⚡ Lab 2 — Create a monitoring dashboard in Grafana and write runbooks (advanced monitoring & incident response)
  • ✎ Exercise 1 — Conduct a fairness audit
Build a portfolio, not just notes

Three real projects you can show in an interview.

Every project is delivered the way the job actually works — phase by phase, with the artifacts a hiring manager asks to see.

Project 1

Multi-Agent Car Insurance Assistant

Plan and deliver a multi-agent assistant for car insurance — scope the use case, define the agent roles, and manage the build as a real AI project rather than a demo.

AI agentsUse case scopingDelivery
Project 2

Real AI Project Simulation & Portfolio

A full simulated AI project with the artifacts to match: risk register, issue log, monitoring dashboard, stakeholder updates and a recorded project walkthrough video.

SimulationDashboardsPortfolio video
Project 3

PMP for an AI Resume Screening System

Take one AI system through all eight phases — pre-project, planning, data acquisition and preparation, model development, integration, testing and QA, deployment, and post-deployment.

8 phasesData prepDeployment
Career prep

Interview Preparation & Q&A

A full interview preparation set for AI project management roles, plus CPMAI exam questions with worked answers so you can talk about AI delivery with confidence.

Interview Q&AExam questions
Real transitions. Real offers.

They did the work.
Here's what happened.

Public reviews from K21 Academy learners across our programs — real names, verified on Google and Trustpilot.

Trustpilot

K21 Academy: The Real Deal for Tech Leaders Transitioning into AI/ML and Cloud

As a VP of Software Engineering making a deliberate career transition into AI/ML and Cloud leadership, I've been extremely selective about where I invest my time and money. Enrolling at K21 Academy has been one of the best professional decisions I've made this year. Since joining, I've completed four courses and successfully passed three Microsoft certification exams: AI-900, AZ-900 and AB-731. What sets K21 apart is the depth of knowledge their trainers bring. The hands-on projects on both Azure and AWS gave me practical experience that actually shows up on a resume and in interviews.

MO
Marcos Oliveira
VP of Software Engineering · California, USA
Google

A one-stop-shop for a great AI/ML career transition experience

K21 Academy is a great professional institution to meet your AI/ML career aspirations, and has the right training, courseware and job application, interview and placement support to help students achieve their goals. I particularly like the quality and depth of the faculty's knowledge, so conducive to learning. With AI/ML growing at such a rapid pace, it is imperative that we get connected with the right industry professionals who bring their experience and expertise to help students transition into a meaningful career.

SS
Sanjeev Saksena
Career transition · Verified Google review
Trustpilot

One of the best learning and professional growth experiences

I am 3 weeks in. The support is extremely awesome for labs, doubts and even resume updates. Atul Sir is always available to address your concerns and provide career guidance. I am extremely impressed with all the live class teachers. The job and resume support is great. The team creates a custom game plan and learning path for everyone. The real-world project experience and hands-on labs are a key differentiator — it sets this program apart from anything else I've tried.

GP
Gaj Paranjape
Verified Trustpilot review · USA
Trustpilot

K21 Academy gave me clarity and confidence in my AI journey

I joined K21 Academy at a time when I felt stuck and unsure about my career direction. Connecting with Shahid was a turning point. He gave me clarity, practical guidance, and renewed confidence. One of K21 Academy's biggest strengths is its curriculum. The content is exhaustive and serves as a one-stop shop. I enrolled across multiple cloud platforms, and despite the significant time commitment, I haven't regretted it for a single moment.

GB
Gunita Bajaj
Verified Trustpilot review · USA
Trustpilot

The K21 experience gave me direction

I recently joined a track course at K21 Academy and it has been a really helpful experience. When I first started learning AI and AWS, I was quite confused about where to begin and what direction to take. The structured curriculum, supportive mentors, and proper guidance have given me a lot of clarity. I also had a very positive experience working with Supriya. She took the time to truly listen to my concerns and challenges, and I really appreciated her patience and attention to detail.

RS
Rahul Syal
Verified Trustpilot review · India
Google

From a non-technical background to a confident AI learner

I decided to explore AI as part of a career change, but coming from a non-technical background made me hesitant to enroll in any course. With the encouragement and support of my husband, I joined K21 Academy run by Atul Kumar and I'm really glad I did. The course is well-structured, catering to both beginners and advanced learners. What stands out the most is the thoughtful design of the program and the strong support system provided by the team. The emphasis on hands-on experience truly enhances the learning process.

MV
Monica Varry
Career changer · Verified Google review
Hear it directly from them

Video stories from K21 learners.

Learners on how they moved into AI, data and cloud roles. Select any video to play it here.

More learners who landed roles through K21 Academy

Steve AI Engineer SJ Salary doubled, husband hired too Debashish AI Engineer (Cloud) Shouvik Senior Enterprise Architect Gopinath Cloud Architect Devesh Solutions Architect Aarti Informatica & AWS Developer Dinesh Tech Program Manager Narasimham Platform Engineer Amol Senior System Engineer Osaghae Edobor Azure Cloud Engineer Srikar AWS Architect Tolu Daramola No IT background → 2 job offers Zeel Software Test Engineer Bezzel Cloud Ops Engineer Etta David DevOps role, under 2 months Winifred Job offer in Canada Bibhu Datta Says the program was worth it Poulami Beginner → Cloud Architect Kennedy Senior Technical Advisor (UK) Pradeep Director of Engineering Meghana Career gap → working with BT Rajalakshmi Career gap → Job @ Infosys Kwame Job offer, relocated to USA
Certification track

Your CPMAI certification roadmap

A complete, structured path to the CPMAI exam — included with the program and mapped to the six phases of the CPMAI methodology.

1
Certification overview
What CPMAI is, who it's for, and what the exam actually tests.
2
Full certification roadmap
The end-to-end route from where you are now to sitting the exam.
3
Course modules — the 6 phases of CPMAI
Each phase of the CPMAI methodology, taught and mapped to your project work.
4
Domain-wise exam prep content
Targeted preparation for every exam domain, so nothing is left to chance.
5
Where to find exam practice questions
The practice sources that matter, and how to use them without wasting weeks.
6
Recommended study plan
A week-by-week plan you can follow alongside a full-time job.
7
Key concepts glossary
Every term you'll be tested on, in plain language, in one place.

Plus 4 full CPMAI mock tests and a complete CPMAI exam question bank with answers.

See pricing →
What the program includes

Everything to lead AI projects — and get certified.

Not a video library. A live, hands-on system with the artifacts to prove it.

Live, Instructor-Led Sessions

Weekly live classes with walkthroughs, Q&A and real project discussion — not passive videos. Every session is recorded and available afterwards.

10 Modules, 105+ Lessons

From PMBOK 7 and Agile foundations through data, MLOps, AI agents, risk, stakeholders and economics — ending with delivery excellence.

CPMAI Certification Roadmap

A full certification track: overview, roadmap, the six CPMAI phases, domain-wise prep, a study plan and a key concepts glossary.

9 Knowledge Checks + 4 Mock Tests

A quiz after every module, plus four full-length CPMAI mock exams and a question bank with worked answers.

3 Portfolio Projects + 6 Labs

Build five AI assistants for your own PM workflow, a multi-agent insurance assistant, run a full project simulation, and take an AI resume screening system through all eight delivery phases.

Interview Preparation

Interview questions and answers for AI project management roles, so the work you've done turns into an offer.

Beginner Courses Included Free

Seven of them: AI, ML & GenAI for Beginners, Cloud for Beginners, AWS for Beginners, Azure for Beginners, Google Cloud for Beginners, plus mock-test sets for AI-900 and the AWS Certified AI Practitioner.

28 Practical Exercises + 7 Hands-On Workshops

Named, hands-on exercises in every module — project charters, sprint role-plays, risk registers, ROI models, fairness audits — plus seven guided hands-on workshops and four Module 9 simulation activities.

Slide Decks for Every Module

The full presentation deck for each module, downloadable and yours to keep as a working reference after the program ends.

Choose your payment plan

Two plans. Pick the one that suits you.

The complete AI Project Management program — live sessions, 10 modules, 3 portfolio projects, beginner courses and the full CPMAI certification track. Founding-member pricing, locked in permanently.

Best Value
Founding Cohort
Standard price $1,997
$1,497
Save $500 — one payment
  • Live instructor-led AI Project Management training
  • 10 modules · 105+ lessons
  • 3 portfolio projects + 7 hands-on workshops
  • Full CPMAI certification roadmap
  • 9 knowledge checks + 4 CPMAI mock tests
  • Interview preparation Q&A
  • 28 practical exercises + module slide decks
  • Beginner courses in AI, cloud & AWS included free
  • All sessions recorded — replay anytime
  • Community access & trainer Q&A
Enrol now — $1,497 →

Secure checkout via SamCart — your founding-member price is applied automatically. Select one-time or installment plan at checkout.

The guarantee — do the work, get the outcome.

Complete the program the way it's designed and you'll finish with three portfolio projects and a clear path to CPMAI — or we keep working with you until you're there.

Attend the live sessions and complete the module exercises
Build all three portfolio projects
Work through the knowledge checks and the 4 mock tests
Ask for support when you need it — don't go silent

Did all that and still stuck? We'll keep coaching you until you're ready. Action-based, no fine print.

Job outcomes

They got hired.
Here's what they said.

Every one of these learners came to K21 Academy with a goal, shipped real projects, landed interviews and got hired.

I'm thrilled to share that I've recently landed a role as a Generative AI Engineer. The hands-on projects let me confidently describe an end-to-end AI solution in the interview. The interviewer was genuinely impressed.

S
Steve
Generative AI Engineer
✓ Google review verified

I've successfully landed a job as an AI Engineer. I worked hands-on with cloud AI services and foundation models, then later received a second offer as a Generative AI Engineer. K21 gave me the skills and the confidence to choose.

DD
Debasish Dash
AI Engineer → Generative AI Engineer
✓ Google review verified

I have finally secured a contract-to-hire role as a Generative AI Engineer. I was deploying a RAG pipeline to a web app during the actual hiring process. The projects I built at K21 were exactly what the company needed.

II
Ike Imala
Generative AI Engineer (contract-to-hire)
✓ Google review verified

Excited to share that I have successfully passed my AI certification exam. A big thank you to the K21 Academy team for their excellent training, well-structured course content, and continuous support. I highly recommend K21 Academy to anyone preparing for AI/ML certifications.

AA
Adnan Ahmed
AI/ML Engineer, certified
✓ Trustpilot verified
Common questions

Before you enroll.

Project managers, scrum masters, delivery leads, business analysts and PMO professionals who want to move into AI projects — plus technical leads who are being asked to run AI delivery. If you're new to project management, the bundled beginner courses bring you up to speed first.
No. You don't need to code. Module 3 gives you the AI/ML fluency a PM needs, and the hands-on labs in Module 5 use no-code and low-code tools like ChatGPT and Zapier to build working assistants for your own workflow.
CPMAI is a certification for managing AI and data projects using a phase-based methodology. The program includes a complete certification roadmap, domain-wise preparation, a study plan, a glossary, an exam question bank and four full mock tests. The exam fee itself is paid directly to the certifying body and is not included in the program price.
Live and instructor-led, so you can ask questions and work through problems with the trainer. Every session is recorded and posted afterwards, so you can catch up or revisit anything at your own pace.
Most learners spend a few hours a week on the live session plus the module exercises and labs. The recommended study plan is built for people working full-time, and the recordings mean you can shift your schedule when work gets busy.
Three portfolio projects — a multi-agent car insurance assistant, a full AI project simulation with dashboards and a walkthrough video, and an AI resume screening system taken through all eight delivery phases — plus five working AI assistants for your own PM workflow, and interview preparation to talk through all of it.
Seven of them: AI, ML & GenAI for Beginners, Cloud for Beginners, AWS for Beginners, Azure for Beginners, Google Cloud for Beginners, plus three-mock-test sets for AI-900 (Azure AI Fundamentals) and the AWS Certified AI Practitioner. All of it is free with your enrollment and unlocks the moment you enrol, so you can finish the foundations before the live cohort begins.

Ready to lead AI projects?

Join the next cohort, build three real projects, and follow a clear path to CPMAI certification.

View pricing & enroll →