Why This Certification Matters

  • Rising Demand for Agile AI Leaders: Organizations adopting AI need project managers who can deliver faster, adaptive, and tech-driven outcomes.

  • Faster Project Delivery: Agile frameworks help teams iterate quickly, reduce delays, and consistently meet evolving stakeholder expectations.

  • Smarter Decision-Making with AI Insights: AI-powered analytics improve planning, forecasting, and risk assessment for more accurate project execution.

  • Improved Collaboration and Transparency: Agile practices foster cross-functional teamwork, clear communication, and real-time progress visibility.

  • Reduced Costs and Risks: Continuous feedback, automation, and incremental releases minimize rework, optimize budgets, and control project risks.

At a Glance: Course + Exam Overview

Program Name
AI+ Agile Project Management Fundamentals™
Included
Instructor-led OR Self-paced course + Official exam + Digital badge
Prerequisites
Basic understanding of project lifecycle and management principles alongside the awareness of agile methodologies like Scrum and Kanban. Introductory knowledge of artificial intelligence and its applications, and ability to address challenges in dynamic environments.
Exam Format
50 questions, 70% passing, 90 minutes, online proctored exam
Delivery
Online labs, projects, case studies
Outcome
Industry-recognized credential + hands-on experience
Who Should Enroll?

Who Should Enroll?

  • Project Managers: Professionals looking to integrate AI tools into Agile workflows to improve planning, forecasting, and delivery outcomes.

  • Scrum Masters: Individuals aim to enhance sprint efficiency, automate reporting, and enable smarter decision-making using AI-driven insights.

  • Product Owners: Professionals interested in leveraging AI for better backlog prioritization, customer insights, and value-based product development.

  • Business Analysts: Those seeking to use AI to analyze requirements, predict risks, and optimize stakeholder communication across projects

  • Agile Team Members: Developers, testers, and designers wanting to streamline collaboration, automate repetitive tasks, and boost productivity with AI support.

Skills You'll Gain

AI-Enabled Agile Planning & Sprint ForecastingIntelligent Backlog Prioritization with Data InsightsAutomated Task Tracking & Workflow OptimizationPredictive Risk Analysis for Project DeliveryAI Tools for Resource Allocation & Capacity PlanningReal-Time Performance Monitoring with Smart DashboardsNatural Language Processing for Stakeholder Communication & ReportingIntegration of AI into ScrumKanban & Hybrid Agile FrameworksDecision Support Systems for Faster Project OutcomesContinuous Improvement Using Data-Driven Retrospectives

What You'll Learn

  • Smart Sprint Planning: Discover how AI-powered insights improve backlog prioritization, sprint forecasting, and resource allocation for predictable delivery.
  • Adaptive Workflow Optimization: Learn to use AI tools to track progress, identify bottlenecks, and automate routine tasks to keep projects moving smoothly.
  • Data-Driven Decision Making: Gain the ability to analyze real-time project metrics, risks, and team performance with AI support for faster, smarter decisions.
  • Enhanced Team Collaboration: Master intelligent communication and reporting tools that improve stakeholder alignment, transparency, and cross-functional teamwork.
  • Predictive Risk Management: Use AI to anticipate delays, budget overruns, and scope creep, enabling proactive planning and effective mitigation strategies.

  • 1.1 Introduction to AI Concepts for Project Managers
  • 1.2 Synergy Between AI and Agile Methodologies
  • 1.3 Case Study: AI-Enhanced Sprint Planning
  • 1.4 Hands-On Session: AI Tools Walkthrough for Sprint Planning and Backlog Grooming

  • 2.1 Understanding Project Data Types and Sources
  • 2.2 Data-Driven Decision Making in Agile
  • 2.3 Case Study: Data-Led Sprint Retrospectives
  • 2.4 Hands-On Simulation Exercise: AI-Driven Sprint Prediction and Metrics Analysis

  • 3.1 Predictive Resource Allocation
  • 3.2 AI-Driven Agile Metrics and Performance Tracking
  • 3.3 Use Cases: Smart Scheduling and Workload Balancing
  • 3.4 Hands-On Session: Managing Team Capacity and Task Distribution Using AI Dashboards

  • 4.1 Foundations of Predictive Modelling
  • 4.2 Forecasting Delays and Resource Shortages
  • 4.3 Case Studies: Early Risk Detection in Agile Projects
  • 4.4 Hands-On Simulation Exercise: Resource Shortage and Timeline Forecasting

  • 5.1 Real-Time Monitoring with AI
  • 5.2 Intelligent Reporting and Stakeholder Communication
  • 5.3 Use Cases: Automated Status Updates and Performance Reviews
  • 5.4 Hands-On Session: Creating AI-Powered Reports and Visual Dashboards

  • 6.1 Ethical AI in Decision-Making
  • 6.2 Bias and Risk in Predictive Models
  • 6.3 Regulatory and Compliance Considerations
  • 6.4 Hands-On Exercise: Evaluating AI Outputs for Fairness and Responsible Use

  • 7.1 Selecting the Right AI Solutions
  • 7.2 Change Management and Stakeholder Adoption
  • 7.3 Case Study: AI-Automated Reporting and Risk Forecasting in Consulting Projects
  • 7.4 Hands-On Simulation Exercise: Tool Evaluation and Vendor Comparison
  • 7.5 Hands-On Exercise: Measuring AI Effectiveness with Project Analytics Platforms

  • 8.1 Autonomous and Self-Optimising Projects
  • 8.2 AI for Remote and Distributed Agile Teams
  • 8.3 Case Studies Inspired by Industry Trends
  • 8.4 Hands-On Simulation Exercise: Designing an AI-Augmented Agile Workflow

Tools You'll Master

ChatGPT
Google Gemini
Microsoft Copilot
Trello AI
Jira Free Tier
ClickUp
Notion AI
Google Sheets with AI Add-ons
Power BI
Tableau Public
Python
Pandas
Scikit-learn
TensorFlow
AutoML Tools
Miro AI
Zapier
Slack AI Integrations
Burndown & Sprint Analytics Dashboards

Prerequisites

  • Basic Understanding of Project Management: Familiarity with project lifecycle and management principles.
  • Introductory Knowledge of Agile: Awareness of agile methodologies like Scrum and Kanban.
  • Familiarity with AI Concepts: Basic knowledge of artificial intelligence and its applications.
  • Problem-Solving Skills: Ability to address challenges in dynamic environments.
  • Team Collaboration Experience: Comfort working in cross-functional, collaborative teams.

Exam Details

Duration

90 minutes

Passing Score

70% (35/50)

Format

50 multiple-choice/multiple-response questions

Delivery Method

Online via proctored exam platform (flexible scheduling)

Exam Blueprint:

  • Fundamentals of AI in Agile Project Management – 7%
  • Data Literacy for Agile Project Managers – 15%
  • AI for Resource and Team Management – 15%
  • Predictive Analytics in Agile Project Management – 15%
  • AI in Project Monitoring and Reporting – 12%
  • Ethics, Bias, and Regulation in AI for Project Management – 12%
  • Evaluating and Implementing AI Tools in Agile Projects – 12%
  • Future Trends and AI in Agile Project Management – 12%

Choose the Format That Fits Your Schedule

What's Included (One-Year Subscription + All Updates):

  • High-Quality Videos, E-book (PDF & Audio), and Podcasts
  • AI Mentor for Personalized Guidance
  • Quizzes, Assessments, and Course Resources
  • Online Proctored Exam with One Free Retake
  • Comprehensive Exam Study Guide
  • Access for Tablet & Phone
Instructor-Led (Live Virtual/Classroom)
  • 1 day (live or virtual) Self-Paced: 8 hours of content
  • Real-time Q&A, peer collaboration, and hands-on labs
  • Led by AI Certified Trainers and delivered through Authorized Training Partners
Self-Paced Online
  • 8 hours of content
  • Learn anywhere, anytime, with modular quizzes to track progress

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Frequently Asked Questions

Yes, you'll gain hands-on experience with AI-powered project management tools, sprint planning techniques, and Agile workflows, enabling you to apply these skills immediately to real projects and team environments.

This course uniquely blends Agile principles with AI capabilities, teaching you how to automate planning, improve forecasting, optimize resources, and make data-driven decisions for smarter and faster project delivery.

You'll work on practical projects such as AI-assisted sprint planning, backlog prioritization, risk prediction, workflow automation, and a capstone project simulating an end-to-end Agile project lifecycle.

The course combines core Agile theory with interactive exercises, real-world case studies, hands-on tool usage, and guided simulations, ensuring you actively practice and apply concepts rather than just learning them passively.

You'll develop in-demand skills in Agile frameworks and AI-driven project management, preparing you for roles such as Scrum Master, Agile Project Manager, Product Owner, or digital transformation lead across industries.

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