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AI+ Project Management Practitioner™

Build stronger project foundations with AI+ Project Management Practitioner ™ by combining AI-assisted planning with practical decision support. Intelligent Project Operations:...
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  • AI-Assisted Project Planning & Estimation
  • Intelligent Scheduling and Workload Balancing
  • Automated Project Tracking and Reporting
  • Predictive Delivery and Risk Signals
  • AI-Powered Decision Support for Projects
  • Workflow and Process Automation
  • Project Data Interpretation and Insights
  • Stakeholder Communication Enablement
  • Secure Handling of Project Information
  • Responsible Application of AI in Project Execution
  • Aspiring Project Managers: Individuals looking to build a strong foundation in project management while gaining exposure to AI-enabled workflows.
  • Early-Career Project Professionals: Project coordinators, analysts, or junior PMs seeking to enhance planning, tracking, and reporting using AI tools.
  • Business and Technical Professionals: Professionals involved in project execution who want to understand how AI can support timelines, resources, and risk awareness.
  • Team Leads and Supervisors: Leaders responsible for overseeing projects who want better visibility and decision support through AI-assisted insights.
  • Professionals Transitioning into AI-Supported Roles: Individuals aiming to stay relevant as project environments increasingly adopt AI-driven tools and data-supported execution.
  • 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.

Duration

90 minutes

Passing Score

70% (35/50)

Format

50 multiple-choice/multiple-response questions

Delivery Method

Online via proctored exam platform (flexible scheduling)

  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

  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

  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

  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

  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

  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

  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

  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

  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

  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

  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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Email: felice.deangelis@proficegroup.it

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