AI+ Agile Project Management Fundamentals™
Transform Project Delivery with AI+ Agile Project Management Fundamentals
Highlights
About this course
- Smart Sprint Planning: Discover how AI-powered insights improve backlog prioritization, sprint forecasting, and resource allocation for predictable delivery.
- Adaptive Workflow Optimization: Learn to use AI tools to track progress, identify bottlenecks, and automate routine tasks to keep projects moving smoothly.
- Data-Driven Decision Making: Gain the ability to analyze real-time project metrics, risks, and team performance with AI support for faster, smarter decisions.
- Enhanced Team Collaboration: Master intelligent communication and reporting tools that improve stakeholder alignment, transparency, and cross-functional teamwork.
- Predictive Risk Management: Use AI to anticipate delays, budget overruns, and scope creep, enabling proactive planning and effective mitigation strategies.
This course includes
Course curriculum
8 chapters · 33 lessons
1.1 Introduction to AI Concepts for Project Managers 1.2 Synergy Between AI and Agile Methodologies 1.3 Case Study: AI-Enhanced Sprint Planning 1.4 Hands-On Session: AI Tools Walkthrough for Sprint Planning and Backlog Grooming
2.1 Understanding Project Data Types and Sources 2.2 Data-Driven Decision Making in Agile 2.3 Case Study: Data-Led Sprint Retrospectives 2.4 Hands-On Simulation Exercise: AI-Driven Sprint Prediction and Metrics Analysis
3.1 Predictive Resource Allocation 3.2 AI-Driven Agile Metrics and Performance Tracking 3.3 Use Cases: Smart Scheduling and Workload Balancing 3.4 Hands-On Session: Managing Team Capacity and Task Distribution Using AI Dashboards
4.1 Foundations of Predictive Modelling 4.2 Forecasting Delays and Resource Shortages 4.3 Case Studies: Early Risk Detection in Agile Projects 4.4 Hands-On Simulation Exercise: Resource Shortage and Timeline Forecasting
5.1 Real-Time Monitoring with AI 5.2 Intelligent Reporting and Stakeholder Communication 5.3 Use Cases: Automated Status Updates and Performance Reviews 5.4 Hands-On Session: Creating AI-Powered Reports and Visual Dashboards
6.1 Ethical AI in Decision-Making 6.2 Bias and Risk in Predictive Models 6.3 Regulatory and Compliance Considerations 6.4 Hands-On Exercise: Evaluating AI Outputs for Fairness and Responsible Use
7.1 Selecting the Right AI Solutions 7.2 Change Management and Stakeholder Adoption 7.3 Case Study: AI-Automated Reporting and Risk Forecasting in Consulting Projects 7.4 Hands-On Simulation Exercise: Tool Evaluation and Vendor Comparison 7.5 Hands-On Exercise: Measuring AI Effectiveness with Project Analytics Platforms
8.1 Autonomous and Self-Optimising Projects 8.2 AI for Remote and Distributed Agile Teams 8.3 Case Studies Inspired by Industry Trends 8.4 Hands-On Simulation Exercise: Designing an AI-Augmented Agile Workflow
AI Tools Used
ChatGPT
Google Gemini
Microsoft Copilot
Trello AI
Jira Free Tier
ClickUp
Notion AI
GitHub Copilot
Google Sheets with AI Add-ons
Power BI
Tableau Public
Python
Pandas
Scikit-learn
TensorFlow
AutoML Tools
Miro AI
Zapier
Slack AI Integrations
Burndown & Sprint Analytics Dashboards
Prerequisites
Exam Details
Mode of Learning
Delivery: SelfPaced
- ✓ Instructor-led OR Self-paced course
- ✓ Official exam
- ✓ Digital badge