Course Outline
Module 1: AI Fundamentals for Project Leadership
Key areas covered:
Insight into Large Language Models (LLMs)
Core AI principles: prompting techniques, hallucination awareness, and context management
Distinguishing between AI systems and conventional automation
Introduction to the course’s toolset (ChatGPT, Claude, Microsoft Copilot)
Live demonstration of AI text generation and interpretation capabilities
Module 2: Strategic Prompt Engineering for Project Management
Key areas covered:
Essential principles of prompt design
Techniques including zero-shot, few-shot, and role-based prompting
Tailoring prompt structures to specific project management objectives
Critically evaluating and iteratively improving AI responses
Hands-on workshops for drafting prompts in realistic project scenarios
Module 3: AI Applications in Project Initiation
Key areas covered:
Drafting project charters with AI assistance
Formulating project goals and scope definitions
Streamlining stakeholder analysis processes
Identifying initial project risks with AI support
Validating AI-generated drafts for precision and thoroughness
Module 4: AI in Planning and Scheduling
Key areas covered:
Generating Work Breakdown Structures (WBS) using AI
Developing milestone schedules and project timelines
Applying AI-assisted estimation methods
Producing recommendations for resource allocation
Optimizing planning deliverables through structured prompting
Module 5: AI in Risk and Issue Management
Key areas covered:
Conducting predictive risk analysis with AI
Compiling risk registers from project descriptions
Facilitating issue classification and triage with AI
Formulating mitigation strategies with AI assistance
Organizing risk data using tables and structured prompt frameworks
Module 6: AI in Stakeholder Communication
Key areas covered:
Automating routine project reporting tasks
Creating executive summaries from raw project data
Adjusting communication tone and style for diverse stakeholder groups
Converting technical details into accessible business updates
Handling sensitive communications with AI support
Module 7: AI Ethics and Governance in Project Contexts
Key areas covered:
Identifying AI bias and hallucination risks
Maintaining ethical standards for AI use in professional settings
Addressing data privacy and GDPR compliance
Establishing AI usage policies within project teams
Implementing human-in-the-loop verification practices
Module 8: AI Toolkits for Project Managers and Adoption Strategy
Key areas covered:
Leveraging Microsoft Copilot across Word, Excel, Teams, and Outlook
Determining when to utilize Copilot versus alternative tools like ChatGPT
Comparative analysis of AI tools for project support
Designing an AI adoption roadmap for project teams
Creating individual AI action plans for personal project workflows
Requirements
Attendees should possess foundational experience within project environments or cross-functional project teams. While a general grasp of core management principles such as scheduling, risk control, and stakeholder interaction is highly beneficial, it serves as a recommendation rather than a strict requirement.
No previous familiarity with Artificial Intelligence applications is necessary for participation.
Testimonials (1)
Understanding that in project management is more about tailoring and assessing each situation than just deciding what to do next.
