Professional Certification Program

Certified AI Project Manager

A delivery-focused certification designed to equip professionals to lead AI-driven projects with confidence, governance, lifecycle control, and real-world execution excellence.

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AI Project Leadership
Lead enterprise AI initiatives with structured planning and execution.
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End-to-End AI Lifecycle
Manage data, model development, deployment, and monitoring effectively.
🛡️
Governance & Risk Control
Ensure ethical AI, compliance, and risk mitigation across projects.

What you will learn

Lead AI Projects
From Concept to Impact

In Certified AI Project Manager (CAPJM), you will gain the skills to plan, execute, and govern AI-driven initiatives across their full lifecycle. This course prepares you to manage data, models, risks, stakeholders, and outcomes for successful enterprise AI delivery.

  • ✔ Understand the AI project landscape, roles, and responsibilities of an AI Project Manager.
  • ✔ Define AI project scope, objectives, stakeholders, and success metrics with clarity.
  • ✔ Manage the end-to-end AI lifecycle including data readiness, model training, deployment, and monitoring.
  • ✔ Apply AI governance, ethics, and risk mitigation practices for responsible AI delivery.
  • ✔ Use modern AI-enabled project management tools and automation for efficiency.
  • ✔ Build real-world capability through case studies and an AI project capstone.
Professionals managing AI projects and analytics dashboards

There are 5 modules in this course

The Certified AI Project Manager (CAPJM) program is designed to help professionals lead AI-driven initiatives end to end — from project definition and data readiness to deployment, governance, and real-world execution through case studies and a capstone.

The AI Project Landscape
Module 1  •  3 lessons
Module details

Build a strong foundation by understanding AI technologies, trends, roles, and responsibilities involved in managing AI projects, including ethics and governance considerations.

  • Understanding AI Technologies and Trends
  • The Role of an AI Project Manager
  • Ethics and Governance in AI Projects
Foundations of AI Project Management
Module 2  •  3 lessons
Module details

Learn how to define AI project scope, align stakeholders, assess data readiness, and establish success metrics for AI initiatives.

  • Defining AI Project Scope and Objectives
  • Stakeholder Alignment and Data Readiness
  • Setting AI-Specific KPIs and Success Metrics
Managing the AI Lifecycle
Module 3  •  3 lessons
Module details

Gain hands-on understanding of how to manage data collection, model training, deployment, monitoring, and continuous improvement across the AI lifecycle.

  • Data Collection, Model Training, and Validation
  • Integration and Deployment Frameworks
  • Monitoring Models and Continuous Improvement
Tools, Techniques, and Automation
Module 4  •  3 lessons
Module details

Explore modern AI-enabled project management tools, automation techniques, and analytics to improve efficiency, documentation, and risk management.

  • AI Project Management Tools and Extensions
  • Using Generative AI for Project Documentation
  • Predictive Analytics in Risk Management
Case Studies and Capstone
Module 5  •  3 lessons
Module details

Apply your learning through real-world AI project case studies and design an AI-driven project plan as part of a practical capstone.

  • AI Project Failure Analysis
  • Designing an AI-Driven Project Plan
  • Capstone Project Presentation
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Earn a career certificate
Add this credential to your LinkedIn profile, resume, and professional portfolio.

What learners say about Certified AI Project Manager (CAPJM)

[Learner Name]
[Role], [Industry/Company]

“[Paste the real testimonial here. Example: CAPJM helped me structure AI projects end-to-end—from scope and data readiness to deployment and monitoring. The governance and risk parts were immediately useful for stakeholder alignment.]”

[Learner Name]
[Role], [Industry/Company]

“[Paste the real testimonial here. Example: The AI lifecycle module clarified what to track at each stage—training, validation, deployment, monitoring—and how to set success metrics that business teams understand.]”

[Learner Name]
[Role], [Industry/Company]

“[Paste the real testimonial here. Example: The tools and automation section saved us time—especially using GenAI for documentation and applying predictive analytics for project risk management.]”

[Learner Name]
[Role], [Industry/Company]

“[Paste the real testimonial here. Example: The case studies and capstone made it practical. I left with a clear project plan and stronger confidence to lead cross-functional AI delivery responsibly.]”

Frequently asked questions

Is this course for project managers or AI engineers?

CAPJM is designed for project/program managers, product leaders, business analysts, and delivery leads who need to manage AI initiatives end-to-end.

You won’t be trained to build models from scratch, but you will learn how to plan, govern, and deliver AI projects with technical teams and stakeholders.

Do I need coding, data science, or ML experience?

No. You don’t need to code. The course focuses on AI project planning, lifecycle management, governance, risk, and execution—so you can lead effectively even if you are non-technical.

You’ll learn the right concepts, questions to ask, and checkpoints to use while working with AI teams.

What will I be able to do after completing CAPJM?

You’ll be able to define AI project scope, set success metrics, align stakeholders, manage the AI lifecycle (data → model → deployment → monitoring), and apply governance and risk controls.

You’ll also be able to create a practical AI project plan and communicate progress and ROI clearly.

Will I learn MLOps and deployment in a practical way?

Yes—at a project leadership level. You’ll understand how deployment pipelines, monitoring, model drift, retraining cycles, and operational handovers impact timelines, risk, and stakeholder expectations.

The focus is on managing delivery and outcomes, not engineering implementation.

How is CAPJM different from a general AI course?

CAPJM is not about AI theory. It is focused on how to run AI projects like a professional—scope, lifecycle checkpoints, governance, risk mitigation, tools, and delivery best practices.

It’s built for execution and real business delivery, not just awareness.

What if my organization’s data is messy or not ready?

That’s common. The course covers data readiness assessment, stakeholder alignment, and how to set realistic AI project scope when data quality or availability is a constraint.

You’ll learn how to de-risk projects early and avoid costly “model-first” failures.

Does the course include case studies and a capstone?

Yes. You’ll work through real-world scenarios including failure analysis, project planning, and a capstone deliverable that helps you apply the framework to an AI initiative.

This helps you move from learning to job-ready execution.

Will I receive a certificate, and can I add it to LinkedIn?

Yes. After completing the program requirements, you’ll receive a digital certificate you can share on LinkedIn and include on your resume or professional portfolio.

Is the course self-paced, and how long do I get access?

Yes, it is self-paced and online. You can complete it based on your schedule and revisit the modules whenever you need a refresher while working on real AI projects.

Can my company enroll a group and get a customized version?

Yes. Organizations often enroll teams to build a shared approach to AI delivery and governance.

For group enrollments or a customized learning path, contact us and we’ll share available options.