Opleiding: AI+ Project Management Practitioner™ eLearning

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.

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.

• AI-Ready Project Foundations:An understanding of how AI supports planning, tracking, and reporting in modern project environments.
• Lower Manual Project Overhead:Reduced administrative effort through AI-assisted coordination and automated project updates.
• Greater Delivery Predictability:Improved visibility into timelines, resource usage, and early risk indicators using AI-driven insights.
• Enhanced Career Relevance:Alignment with project roles that increasingly value AI-supported workflows and data-aware execution.
• Confident Leadership in AI-Supported Teams:The ability to guide teams using AI-enhanced dashboards, automation, and real-time project intelligence.

• 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

• 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

• 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

• 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

• 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

• 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

• 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

• 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

• 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

• 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

• 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

• 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

Online proctored exam included, with one free retake.
Exam format: 50 questions, 70% passing, 90 minutes, online proctored exam

Access to all materials and exams is provided for 365 days after delivery.

De OCICT maatwerk-methode houdt in dat op basis van de behoefte van de klant - en indien nodig na een intakegesprek - een individueel opleidingstraject wordt opgesteld. De trainingen worden veelal individueel gevolgd, zodat iedere training een maatwerktraject is. Klassikale trainingen zijn natuurlijk mogelijk, mits ze aansluiten bij de leerbehoeften van de deelnemers / opdrachtgever.

Alle onderdelen van de training kennen een voortdurende wisselwerking tussen theorie en praktijk. De inhoud van de training kan vooraf per cursist worden aangepast en tijdens de cursus worden bijgesteld. De focus ligt op maatwerk: het traject wordt afgestemd op de doelstellingen van de deelnemer(s) en/of opdrachtgever, ongeacht of het individueel of klassikaal wordt aangeboden.