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AI+ Agile Project Management Fundamentals™

Course code: NPAP110002

Transform Project Delivery with AI+ Agile Project Management Fundamentals

Sprint Planning, sharpened by AI: Backlog prioritization, sprint forecasting, and resource allocation all improve, supporting more predictable delivery.
Smoother Workflows Through AI: AI tools track progress, flag bottlenecks, and take over routine tasks, keeping projects moving smoothly.
Decisions Grounded in Data: Real-time project metrics, risks, and team performance become easier to read with AI, leading to quicker, better-informed choices.
Collaboration That Works Better: Intelligent communication and reporting tools strengthen stakeholder alignment, transparency, and cross-functional teamwork.
Staying Ahead of Risk: Delays, budget overruns, and scope creep become easier to catch early with AI, supporting proactive planning and stronger mitigation.
75 EUR

91 EUR including VAT

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Course dates

Starting date: Upon request

Guaranteed

Type: Self-paced

Course duration: 8 hours

Language: en

Price without VAT: 285 EUR

Register

Starting date: Upon request

Guaranteed

Type: Self-paced

Course duration: 8 hours

Language: en

Price without VAT: 75 EUR

Register

Starting
date		 Place
Type Course
duration		 Language Price without VAT
G Upon request Self-paced 8 hours en 285 EUR Register
G Upon request Self-paced 8 hours en 75 EUR Register
G Guaranteed course

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Course description

AI Integration in Agile Planning

Learn how to incorporate AI tools into sprint planning, backlog grooming, and resource allocation to improve forecasting accuracy and team productivity.

Smart Workflow Automation with AI

Gain expertise in automating repetitive project tasks such as status tracking, reporting, and documentation, enabling teams to focus on high-value work.

Data-Driven Decision Making

Understand how AI-powered analytics can help interpret project metrics, predict risks, and support faster, evidence-based decisions throughout the project lifecycle.

AI-Enhanced Risk and Issue Management

Discover how intelligent tools can identify potential bottlenecks, delays, and dependencies early, allowing proactive mitigation and smoother delivery.

Natural Language Processing for Collaboration

Learn to use NLP-based assistants to summarise meeting notes, extract action items, and improve communication across distributed Agile teams.

Predictive Sprint Performance Tracking

Master AI techniques to forecast sprint outcomes, measure velocity trends, and continuously optimise team performance.

Course structure

Module 1: Fundamentals of AI in Agile Project Management

  • 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

Module 2: Data Literacy for Agile Project Managers

  • 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

Module 3: AI for Resource and Team Management

  • 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

Module 4: Predictive Analytics in Agile Project Management

  • 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

Module 5: AI in Project Monitoring and Reporting

  • 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

Module 6: Ethics, Bias, and Regulation in AI for Project Management

  • 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

Module 7: Evaluating and Implementing AI Tools in Agile Projects

  • 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

Module 8: Future Trends and AI in Agile Project Management

  • 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

Prerequisites

  • Project Management Basics: A working familiarity with the project lifecycle and its core principles. 
  • Exposure to Agile Frameworks: Some awareness of methodologies such as Scrum and Kanban. 
  • AI Concept Familiarity: A general sense of artificial intelligence and how it’s applied. 
  • Comfort with Problem-Solving: The ability to navigate challenges in fast-changing environments. 
  • Experience Working Across Teams: Ease collaborating within cross-functional group settings. 

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