About This Course
- 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
Course Information
Course Code
AI+ Project Management Practitioner™
Duration
Self-Paced: 40 hours of content
Delivery
Self Paced
Exam Voucher
Included
Course Curriculum
- 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
Get the Full Syllabus as a PDF
Curriculum, exam format & everything included — sent straight to your inbox.
All You Need to Know
Who Should Attend
- 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.
Prerequisites
- 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.
Examination
Duration
90 minutes
Passing Score
70% (35/50)
Format
50 multiple-choice/multiple-response questions
Delivery Method
Online via proctored exam platform (flexible scheduling)
Frequently Asked Questions
This is generally the more advanced, practitioner-level credential building on the foundational AI+ Project Manager certification — confirm the exact prerequisite structure with your course advisor.
Experienced project managers looking to deepen their practical application of AI within project delivery.
This is commonly structured as a progression — check current prerequisites before enrolling.
AI CERTs exams are typically online, proctored, combining multiple-choice questions with practical exercises.
Yes, AI CERTs certifications are designed to be globally recognised across industries.