x

AI+ Project Management Practitioner™

AI+ Project Management Practitioner™
  • 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.
AVALIABLE AT COMPUNET LIMITED Enroll Now Enroll Now

Certificate Code

AP 2601

Exam Format

AI-Driven Remote Exam Proctoring

Course Overview

Important details and certification information

Instructor-led OR Self-paced course + Official exam + Digital badge
Instructor-Led: 3 Days (live or virtual)
Foundational knowledge of project management practices, familiarity with common project tools, and basic understanding of AI concepts such as machine learning and predictive analytics. Ideal for professionals with project exposure seeking to apply AI to improve project efficiency and delivery.
50 questions, 70% passing, 90 minutes, online proctored exam

Certification Modules

  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

AI Tools Covered

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
Enroll Now Enroll Now