Course Outline
Module 1: AI Foundations for Project Managers
Key areas of focus include: Understanding Large Language Models (LLMs); exploring core AI concepts such as prompting, hallucination, and context; distinguishing between AI systems and traditional automation; reviewing the AI tools featured in the course (ChatGPT, Claude, Microsoft Copilot); and demonstrating how AI generates and interprets textual data.
Module 2: Prompt Engineering for Project Management
This module covers the fundamentals of prompt design, including zero-shot, few-shot, and role-based prompting techniques. Participants will learn to structure prompts for specific project management tasks, evaluate and refine AI responses, and apply these skills through practical exercises focused on real-world project scenarios.
Module 3: AI in Project Initiation
Topics include AI-assisted drafting of project charters, generating project objectives and scope statements, and automating stakeholder analysis. The session also explores AI-supported identification of early project risks and methods for evaluating AI-generated outputs for both accuracy and completeness.
Module 4: AI in Planning and Scheduling
This section focuses on generating Work Breakdown Structures (WBS) and creating milestone plans and project timelines. Participants will examine AI-assisted estimation techniques, explore resource allocation suggestions, and learn how to refine planning outputs using structured prompting methods.
Module 5: AI in Risk and Issue Management
Learn about predictive risk analysis using AI, generating risk registers from project descriptions, and AI-assisted issue classification and triage. The module also covers developing mitigation strategies with AI support and structuring risk information effectively using tables and prompts.
Module 6: AI in Stakeholder Communication
This module explores automating project reporting, generating executive summaries from project data, and adapting tone and style for diverse stakeholder audiences. It also addresses transforming technical details into business-friendly updates and managing sensitive communications with AI assistance.
Module 7: AI Ethics and Governance in Projects
Key discussions include understanding risks associated with AI bias and hallucination, responsible AI usage in professional settings, and data privacy considerations within the context of GDPR. Participants will also learn to define AI usage policies for project teams and implement human-in-the-loop validation practices.
Module 8: AI Tools for Project Managers and Adoption Strategy
This final module covers the practical use of Microsoft Copilot in Word, Excel, Teams, and Outlook. It provides guidance on choosing between Copilot and other tools like ChatGPT, compares various AI options for project support, and outlines strategies for building an AI adoption roadmap and a personal AI action plan for project work.
Requirements
Attendees are expected to have foundational experience operating within project environments or teams. A general understanding of core project management disciplines, including planning, risk management, and stakeholder engagement, is recommended for optimal participation.
No prior expertise with Artificial Intelligence tools is necessary for this course.
Testimonials (1)
Understanding that in project management is more about tailoring and assessing each situation than just deciding what to do next.
