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AI+ Project Management Practitioner™

# AP 2601

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.

$195.00

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Hands-on Practices

Prerequisites

  • Basic understanding of project management principles and processes.
  • Familiarity with project management tools and techniques.
  • General knowledge of artificial intelligence concepts (machine learning, predictive analytics, etc.).
  • Experience in managing or overseeing projects, preferably in a technical or business context.
  • Willingness to learn and apply AI-based tools to enhance project management efficiency.

Exam Details

  • Modules (10)
  • Examination (1)
  • 50 MCQs, 90 minutes
  • Passing Score (70% (35/50))

Exam Blueprint

ModulesPercentage
Project Management Overview10
Introduction to AI and ML10
Data Driven Decision Making10
AI – Driven Project Risk Management 10
Planning Project Work Breakdown and Structuring and Project Scheduling by AI 10
Effective Project Budgeting Using AI10
AI for Planning Human Resources10
Stakeholder Management Using AI10
AI – Based Project Monitoring10
Transformative Role of Project Management 10

Self Study Materials Included

Videos
Engaging visual content to enhance understanding and learning experience.
Podcasts
Insightful audio sessions featuring expert discussions and real-world cases.
E-Books
Comprehensive digital guides offering in-depth knowledge and learning support.
Audiobooks
Listen and learn anytime with convenient audio-based knowledge sharing.
Module Wise Quizzes
Interactive assessments to reinforce learning and test conceptual clarity.
Additional Resources
Supplementary references and list of tools to deepen knowledge and practical application.
Hands-on
Practical experience through real-world exercises, case studies, and applied learning.

Tools You'll Master

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

What Will You Learn?

AI in Project Planning
Learn how AI improves scheduling, estimation accuracy, and task prioritization across projects.
Automated Project Tracking
Understand AI-driven tools for real-time status updates, progress monitoring, and reporting.
Predictive Risk Awareness
Identify potential project delays and risks early using AI-generated insights and patterns.
Resource and Workflow Optimization
Apply AI to balance workloads, optimize resources, and streamline everyday project operations.
Responsible AI Usage in Projects
Develop awareness of ethical AI practices, data governance, and compliance in project environments.

Certification Modules

Module 1: Project Management Overview
  1. 1.1 Introduction to Project Management
  2. 1.2 Project Management Lifecycle
  3. 1.3 Advanced Project Management Tasks
  4. 1.4 Project Management Frameworks
  5. 1.5 Project Manager’s Roles and Responsibilities
Module 2: Introduction to AI and ML
  1. 2.1 Introduction to Artificial Intelligence (AI)
  2. 2.2 Introduction to Machine Learning (ML)
  3. 2.3 Neural Networks
  4. 2.4 AI and ML Applications and Trends
  5. 2.5 Case Studies on AI and ML Projects
Module 3: Data Driven Decision Making
  1. 3.1 The Importance of Data in Artificial Intelligence
  2. 3.2 Data Analysis Techniques
  3. 3.4 Applying Data Insights to Project Decisions
  4. 3.5 Tools for Data Visualization and Reporting
  5. 3.6 Challenges and Best Practices
Module 4: AI-Driven Project Risk Management
  1. 4.1 AI in Risk Management – An Introduction
  2. 4.2 AI for Risk Mitigation and Response
  3. 4.3 AI for Financial and Resource Risk Management
  4. 4.4 AI in Risk Management: The Future Scope
  5. 4.5 Case Study – AI-based Project Risk Management
Module 5: Planning Project Work Breakdown and Structuring and Project Scheduling by AI
  1. 5.1 Introduction to Work Breakdown Structure (WBS)
  2. 5.2 AI for WBS Creation
  3. 5.3 AI in Project Scheduling
  4. 5.4 AI for Resource-Constrained Scheduling
  5. 5.5 Case Studies: AI-based WBS and AI Algorithms for Project Scheduling
Module 6: Effective Project Budgeting Using AI
  1. 6.1 Introduction to AI in Budgeting
  2. 6.2 AI for Estimating Costs and Budget Allocation
  3. 6.3 AI for Budget Optimization
  4. 6.4 Future of AI in Project Budgeting
  5. 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
  1. 7.1 Introduction to AI in Human Resource Planning
  2. 7.2 AI for Workforce Allocation
  3. 7.3 AI in Skill Matching and Employee Performance Analysis
  4. 7.4 The Future of AI in Human Resource Planning
  5. 7.5 Case Studies: Designing AI-Based Models for HR Planning
Module 8: Stakeholder Management Using AI
  1. 8.1 Introduction to Stakeholder Management and AI
  2. 8.2 Identifying and Categorizing Stakeholders Using AI
  3. 8.3 Stakeholder Conflicts Management with AI
  4. 8.4 Ethics and Future Prospects in AI-based Stakeholder Management
  5. 8.5 Case Studies: AI Tools for Stakeholder Management
Module 9: AI-based Project Monitoring
  1. 9.1 Introduction to Project Monitoring and AI
  2. 9.2 AI-based Tools for Monitoring Project Progress
  3. 9.3 AI for Risk Monitoring
  4. 9.4 Case Studies: AI Tools for Project Monitoring
Module 10: Transformative Role of Project Management
  1. 10.1 Current State of AI in Project Management
  2. 10.2 Ethical Considerations in AI-Based Project Management
  3. 10.3 Technical Challenges in AI Integration
Additional Module: AI Agents for Project Management Practitioner
  1. 1. Understanding AI Agents
  2. 2. How Does an AI Agent Work
  3. 3. Applications and Trends of AI Agents in Project Management
  4. 4. Core Characteristics of AI Agents
  5. 5. Significance of AI Agents in Project Management
  6. 6. Types of AI Agents
  7. 7. Case Study-AI Agents for Agile Project Delivery – Atlassian in Action
  8. 8. Hands-On Activity

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Industry Opportunities after Certification Completion

Median Salaries
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With AI+ Project Management Practitioner™
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% Difference
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Begin your Journey
AI-Augmented Delivery Professional

Work alongside project leaders using AI-powered dashboards and insights to support planning, coordination, and delivery tracking.

Project Intelligence Associate

Translate project data into meaningful signals using AI-assisted reporting, helping teams anticipate delays and workload challenges.

Operations and Execution Analyst

Apply AI tools to improve task flow, resource visibility, and operational rhythm across ongoing initiatives.

Transformation Program Support Specialist

Assist digital transformation efforts by integrating AI-enabled project workflows into existing delivery and governance structures.

Future-Ready Project Practitioner

Build early expertise in AI-supported project environments, creating a strong foundation for advanced project or transformation roles.

Trusted Reviews by Our Learners

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Frequently Asked Questions

Yes, the certification includes hands-on project scenarios using realistic project data. You’ll be able to apply AI-supported planning, tracking, and reporting techniques directly in active project environments.
This course uniquely focuses on applying AI to everyday project workflows—planning, scheduling, monitoring, and risk awareness—rather than abstract theory, making it practical for real project execution.
You’ll work on AI-assisted project planning models, automated status reporting workflows, risk identification scenarios, and intelligent project support tools based on real delivery challenges.
The course combines guided modules, interactive examples, and applied project exercises that reinforce learning through hands-on practice and real-world project use cases.
It builds practical experience with AI-enabled project tools, data-informed decision-making, and automation—skills increasingly expected in modern project coordination and management roles.
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