AI for Project Managers: Prompt Engineering & Use Cases

AI for Project Managers: Prompt Engineering & Use Cases

Instructors: Ahmed Hassan

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2 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

5 hours to complete

Flexible schedule

Learn at your own pace

2 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

5 hours to complete

Flexible schedule

Learn at your own pace

What you'll learn

Core technologies behind generative AI, including LLMs, natural language processing, and predictive analytics.
High-value use cases across the project lifecycle — initiation, planning, execution, monitoring, and closing.
How GenAI tools assist with common project management activities such as generating charters, meeting summaries, and status reports.
Prompt engineering techniques to interact effectively with AI tools and generate reliable outputs.

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There are 2 modules in this course

Generative AI is rapidly transforming how project managers plan, monitor, and deliver complex initiatives. As organizations increasingly adopt AI-driven tools, project professionals must learn how to leverage these technologies to improve efficiency, enhance decision-making, and deliver projects more predictably. This course provides project managers, PMO leaders, and delivery professionals with a practical introduction to applying generative AI (GenAI) in project and portfolio management.

Throughout the course, you will gain hands-on experience designing AI-assisted workflows through demonstrations, guided exercises, and a course-end project. You will learn how GenAI tools assist with generating project charters, meeting summaries, status reports, and other project artifacts, while also supporting predictive delivery, portfolio prioritization, resource optimization, and strategic governance within a PMO. By the end of the course, you will be able to identify practical GenAI use cases within your own project environments, apply prompt engineering techniques to generate project artifacts, and leverage AI insights to improve delivery forecasting and portfolio management decisions.

This module introduces the foundational concepts of generative AI and explores how these technologies can enhance project and portfolio management practices. Learners will gain a practical understanding of how large language models (LLMs), natural language processing, and AI-driven analytics can support everyday project management activities such as reporting, documentation, communication, and risk analysis. The module also highlights high-value GenAI use cases across the project lifecycle from initiation and planning to monitoring and closing, showing how AI can reduce administrative overhead and improve decision support. Finally, learners will explore prompt engineering techniques that enable project managers to effectively interact with AI tools and generate reliable project artifacts such as risk registers, status reports, and project plans.

What's included

11 videos2 readings1 assignment1 peer review2 discussion prompts

11 videosTotal 79 minutes

Introduction to the Course5 minutes
Module Introduction4 minutes
What is Generative AI and How It Works6 minutes
The Current State of AI in Project Management and PMOs8 minutes
Generating Project Status Reports Using GenAI9 minutes
AI for Project Initiation and Planning8 minutes
AI for Execution and Monitoring Activities7 minutes
Generating Risk Registers and Stakeholder Communications8 minutes
Prompt Engineering Fundamentals for Project Managers6 minutes
Chain-of-Thought Prompting for Complex Project Analysis7 minutes
Writing Effective Prompts for Project Deliverables12 minutes

2 readingsTotal 10 minutes

Welcome to the Course: Course Overview5 minutes
ChatGPT prompts for project management (2026)5 minutes

1 assignmentTotal 20 minutes

Foundations and High-Value GenAI Use Cases for Project Managers20 minutes

1 peer reviewTotal 10 minutes

Hands-On-Learning: Generating Project Artifacts Using GenAI10 minutes

2 discussion promptsTotal 10 minutes

Managing Risks of AI in Project Workflows5 minutes
Identifying High-Impact AI Automation Opportunities5 minutes

This module focuses on how generative AI can enhance project delivery predictability and support strategic decision-making at both the project and portfolio levels. Learners will explore how AI tools analyze project schedules, historical performance data, and project documentation to identify delivery risks, forecast schedule delays, and provide early warning signals before problems escalate. The module also introduces AI-assisted approaches to risk management, scope change analysis, and portfolio governance. Participants will learn how GenAI can help project managers evaluate change requests, simulate delivery scenarios, and optimize resource allocation across multiple projects. Through practical demonstrations and applied exercises, learners will develop the skills required to use AI tools to improve forecasting accuracy, strengthen portfolio visibility, and support better strategic investment decisions.

What's included

9 videos1 reading1 assignment2 peer reviews2 discussion prompts

9 videosTotal 64 minutes

Module Introduction3 minutes
Predictive Scheduling and Budgeting Using AI13 minutes
Forecasting Milestone Delays and exceeding Budget with AI Insights5 minutes
AI-Driven Risk Identification6 minutes
Evaluating Scope Changes Using AI Analysis5 minutes
Creating an AI-Generated Risk Register12 minutes
AI-Powered Portfolio Prioritization7 minutes
Resource Optimization Across Project Portfolios6 minutes
Running a Portfolio Prioritization Simulation with GenAI7 minutes

1 readingTotal 5 minutes

How Generative AI Can Revolutionize Project Scheduling5 minutes

1 assignmentTotal 20 minutes

Predictive Delivery and Strategic Portfolio Management with GenAI20 minutes

2 peer reviewsTotal 70 minutes

Hands-On-Learning: Forecasting Delivery Risks Using AI10 minutes
Project: AI-Enabled Project Delivery Plan60 minutes

2 discussion promptsTotal 10 minutes

Using Predictive Analytics to Improve Project Forecasting5 minutes
Challenges in AI-Driven Portfolio Prioritization5 minutes

Instructors

Ahmed Hassan

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