AI+ Project Management Practitioner (AP 2601 Self-Paced Training)
Ziele der Schulung
The AI+ Project Management Practitioner certification equips learners to enhance traditional project management with AI-enabled planning, scheduling, data-driven decision support, predictive insights, governance awareness, and leadership foundations for AI-augmented project environments. It focuses on reducing manual effort, improving consistency, and integrating AI tools for risk detection, resource optimization, and stakeholder alignment. What Will You Learn? You’ll learn how AI improves project planning, automated tracking, predictive risk awareness, workflow optimization, and responsible use of AI in project settings.
Zielgruppe Seminar
Aspiring project managers, early-career project professionals (e.g., coordinators, analysts), business and technical professionals involved in project execution, team leads/supervisors seeking better visibility and decision support with AI tools, and professionals transitioning into AI-supported roles in project environments.
Voraussetzungen
- Basic understanding of project management principles and processes
- Familiarity with project management tools and techniques
- General knowledge of AI concepts (e.g., machine learning, predictive analytics)
- Experience managing or overseeing projects, preferably in technical/business contexts
- Willingness to learn and apply AI-based tools to enhance project efficiency
Seminarinhalt
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 Technique
- 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 Budgeting
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
- Understanding AI Agents
- How Does an AI Agent Work
- Applications and Trends of AI Agents in Project Management
- Core Characteristics of AI Agents
- Significance of AI Agents in Project Management
- Types of AI Agents
- Case Study-AI Agents for Agile Project Delivery – Atlassian in Action
- Hands-On Activity
Hinweise
Prüfung und Zertifizierung
- 50 multiple-choice questions
- 90 minutes
- Passing Score: 70% (35/50)
- Proctored online exam as part of the certification process
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