AI+ Project Management Practitioner™ eLearning

Build stronger project foundations with AI+ Project Management Practitioner ™ by combining AI-assisted planning with practical decision support.

• Intelligent Project Operations: Discover how AI enhances planning, scheduling, task prioritization, and progress tracking to reduce manual effort and improve project consistency.
• Predictive Planning & Resource Optimization: Use data-driven insights for timeline forecasting, workload balancing, capacity planning, and early risk detection to keep projects on track.
• Governance, Compliance & Risk Awareness: Understand how AI supports documentation accuracy, change control, audit readiness, and ongoing risk monitoring in project environments.
• Leadership Foundations for AI-Augmented Projects: Build skills to lead teams using AI-enabled workflows, including automated reporting, real-time insights, and improved stakeholder alignment.

Module 1: Project Management Overview

• 1.1 Introduction to Project Management
• 1.2 Project Management Lifecycle
• 1.3 Advanced Project Management Tasks
• 1.4 Project Management Frameworks
• 1.5 Project Manager’s Roles and Responsibilities

Module 2: Introduction to AI and ML

• 2.1 Introduction to Artificial Intelligence (AI)
• 2.2 Introduction to Machine Learning (ML)
• 2.3 Neural Networks
• 2.4 AI and ML Applications and Trends
• 2.5 Case Studies on AI and ML Projects

Module 3: Data Driven Decision Making

• 3.1 The Importance of Data in Artificial Intelligence
• 3.2 Data Analysis Techniques
• 3.4 Applying Data Insights to Project Decisions
• 3.5 Tools for Data Visualization and Reporting
• 3.6 Challenges and Best Practices

Module 4: AI-Driven Project Risk Management

• 4.1 AI in Risk Management – An Introduction
• 4.2 AI for Risk Mitigation and Response
• 4.3 AI for Financial and Resource Risk Management
• 4.4 AI in Risk Management: The Future Scope
• 4.5 Case Study – AI-based Project Risk Management

Module 5: Planning Project Work Breakdown and Structuring and Project Scheduling by AI

• 5.1 Introduction to Work Breakdown Structure (WBS)
• 5.2 AI for WBS Creation
• 5.3 AI in Project Scheduling
• 5.4 AI for Resource-Constrained Scheduling
• 5.5 Case Studies: AI-based WBS and AI Algorithms for Project Scheduling

Module 6: Effective Project Budgeting Using AI

• 6.1 Introduction to AI in Budgeting
• 6.2 AI for Estimating Costs and Budget Allocation
• 6.3 AI for Budget Optimization
• 6.4 Future of AI in Project Budgeting
• 6.5 Case  Study:  AI  Algorithms  for  Project  Scheduling, AI- Based Model for Estimating Costs and Budget Allocation

Module 7: AI for Planning Human Resources

• 7.1 Introduction to AI in Human Resource Planning
• 7.2 AI for Workforce Allocation
• 7.3 AI in Skill Matching and Employee Performance Analysis
• 7.4 The Future of AI in Human Resource Planning
• 7.5 Case Studies: Designing AI-Based Models for HR Planning

Module 8: Stakeholder Management Using AI

• 8.1 Introduction to Stakeholder Management and AI
• 8.2 Identifying and Categorizing Stakeholders Using AI
• 8.3 Stakeholder Conflicts Management with AI
• 8.4 Ethics and Future Prospects in AI-based Stakeholder Management
• 8.5 Case Studies: AI Tools for Stakeholder Management

Module 9: AI-based Project Monitoring

• 9.1 Introduction to Project Monitoring and AI
• 9.2 AI-based Tools for Monitoring Project Progress
• 9.3 AI for Risk Monitoring
• 9.4 Case Studies: AI Tools for Project Monitoring

Module 10: Transformative Role of Project Management

• 10.1 Current State of AI in Project Management
• 10.2 Ethical Considerations in AI-Based Project Management
• 10.3 Technical Challenges in AI Integration

Additional Module: AI Agents for Project Management Practitioner

• 1. Understanding AI Agents
• 2. How Does an AI Agent Work
• 3. Applications and Trends of AI Agents in Project Management
• 4. Core Characteristics of AI Agents
• 5. Significance of AI Agents in Project Management
• 6. Types of AI Agents
• 7. Case Study-AI Agents for Agile Project Delivery – Atlassian in Action
• 8. Hands-On Activity

Tools you will explore

• Python for Project Analytics
• Machine Learning Libraries for Project Insights (Scikit-learn, TensorFlow)
• Project Data Handling Tools (Pandas, NumPy)
• Visualization Platforms for Project Dashboards (Power BI, Tableau)
• Project Data Storage using SQL & NoSQL Databases
• APIs for Project and Workflow Integration
• Cloud Platforms for AI-Enabled Project Management (AWS & Azure Services)
• OpenAI & LangChain for AI-Assisted Project Tools

Online proctored exam included, with one free retake.
Exam format: 50 questions, 70% passing, 90 minutes, online proctored exam

Access to all materials and exams is provided for 365 days after delivery.

Instructor-led OR Self-paced course + Official exam + Digital badge