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AI+ Agile Project Management Fundamentals™

AI+ Agile Project Management Fundamentals™
  • 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.
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Certificate Code

AP 110002

Exam Format

AI-Driven Remote Exam Proctoring

Course Overview

Important details and certification information

Instructor-led OR Self-paced course + Official exam + Digital badge
Instructor-Led: 3 Days (live or virtual)
Basic understanding of project lifecycle and management principles alongside the awareness of agile methodologies like Scrum and Kanban. Introductory knowledge of artificial intelligence and its applications, and ability to address challenges in dynamic environments.
50 questions, 70% passing, 90 minutes, online proctored exam

Certification Modules

  1. 1.1 Introduction to AI Concepts for Project Managers
  2. 1.2 Synergy Between AI and Agile Methodologies
  3. 1.3 Case Study: AI-Enhanced Sprint Planning
  4. 1.4 Hands-On Session: AI Tools Walkthrough for Sprint Planning and Backlog Grooming

  1. 2.1 Understanding Project Data Types and Sources
  2. 2.2 Data-Driven Decision Making in Agile
  3. 2.3 Case Study: Data-Led Sprint Retrospectives
  4. 2.4 Hands-On Simulation Exercise: AI-Driven Sprint Prediction and Metrics Analysis

  1. 3.1 Predictive Resource Allocation
  2. 3.2 AI-Driven Agile Metrics and Performance Tracking
  3. 3.3 Use Cases: Smart Scheduling and Workload Balancing
  4. 3.4 Hands-On Session: Managing Team Capacity and Task Distribution Using AI Dashboards

  1. 4.1 Foundations of Predictive Modelling
  2. 4.2 Forecasting Delays and Resource Shortages
  3. 4.3 Case Studies: Early Risk Detection in Agile Projects
  4. 4.4 Hands-On Simulation Exercise: Resource Shortage and Timeline Forecasting

  1. 5.1 Real-Time Monitoring with AI
  2. 5.2 Intelligent Reporting and Stakeholder Communication
  3. 5.3 Use Cases: Automated Status Updates and Performance Reviews
  4. 5.4 Hands-On Session: Creating AI-Powered Reports and Visual Dashboards

  1. 6.1 Ethical AI in Decision-Making
  2. 6.2 Bias and Risk in Predictive Models
  3. 6.3 Regulatory and Compliance Considerations
  4. 6.4 Hands-On Exercise: Evaluating AI Outputs for Fairness and Responsible Use

  1. 7.1 Selecting the Right AI Solutions
  2. 7.2 Change Management and Stakeholder Adoption
  3. 7.3 Case Study: AI-Automated Reporting and Risk Forecasting in Consulting Projects
  4. 7.4 Hands-On Simulation Exercise: Tool Evaluation and Vendor Comparison
  5. 7.5 Hands-On Exercise: Measuring AI Effectiveness with Project Analytics Platforms

  1. 8.1 Autonomous and Self-Optimising Projects
  2. 8.2 AI for Remote and Distributed Agile Teams
  3. 8.3 Case Studies Inspired by Industry Trends
  4. 8.4 Hands-On Simulation Exercise: Designing an AI-Augmented Agile Workflow

AI Tools Covered

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
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