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: 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.
Módulos
- 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
Herramientas de IA
- 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