Course Outline
Module 1: Foundational AI Principles for Project Management Professionals
Subtopics:
Analysis of Large Language Models (LLMs) for government applications
Core AI principles: prompt engineering, hallucination mitigation, and context management
Distinguishing AI systems from conventional automation methods
Survey of AI platforms relevant to public sector workflows (ChatGPT, Claude, Microsoft Copilot)
Demonstration of text generation and interpretation capabilities
Module 2: Strategic Prompt Engineering for Project Governance
Subtopics:
Principles of effective prompt architecture
Application of zero-shot, few-shot, and role-based prompting techniques
Structuring prompts for standardized project management tasks for government operations
Methods for validating and refining AI-generated responses
Practical exercises: drafting prompts for complex project scenarios
Module 3: AI Integration in Project Initiation Processes
Subtopics:
AI-assisted drafting of project charters
Synthesis of project objectives and scope definitions
Automation of stakeholder analysis frameworks
Identification of initial project risks through AI support
Critical evaluation of AI outputs for factual accuracy and completeness
Module 4: AI Applications in Planning and Scheduling
Subtopics:
Generation of Work Breakdown Structures (WBS) using AI
Development of milestone plans and project timelines
AI-supported estimation methodologies
Generation of resource allocation recommendations
Optimization of planning outputs via structured prompt techniques
Module 5: AI in Risk and Issue Management Protocols
Subtopics:
Predictive risk analysis leveraging AI capabilities
Construction of risk registers from project narratives
AI-assisted classification and triage of operational issues
Formulation of mitigation strategies with AI assistance
Organization of risk data using structured tables and prompts
Module 6: AI in Stakeholder Communication and Reporting
Subtopics:
Automation of routine project reporting functions
Creation of executive summaries from raw project data
Adaptation of communication tone for various stakeholder groups
Translation of technical details into clear, business-oriented updates for government audiences
Management of sensitive communications with AI support
Module 7: AI Ethics, Governance, and Compliance in Public Projects
Subtopics:
Analysis of AI bias and hallucination risks in professional settings
Guidelines for responsible AI deployment in public sector environments
Data privacy considerations and compliance with GDPR and federal regulations
Establishment of AI usage policies within project teams
Implementation of human-in-the-loop validation procedures
Module 8: AI Tooling and Strategic Adoption for Project Teams
Subtopics:
Utilization of Microsoft Copilot across Word, Excel, Teams, and Outlook
Determining appropriate use cases for Copilot versus ChatGPT and other platforms
Comparative analysis of AI tools for project management support
Development of an AI adoption roadmap for project organizations for government implementation
Creation of individual AI action plans for professional development
Requirements
Participants are expected to possess fundamental experience in project environments or collaborative project teams. A working knowledge of general project management concepts, including planning, risk management, and stakeholder communication, is recommended.
No prior experience with Artificial Intelligence tools is required.
Testimonials (1)
Understanding that in project management is more about tailoring and assessing each situation than just deciding what to do next.
