Mastering ChatGPT Skills Prompt Engineering for Project Planning and Analysis

Generative AI is transforming how projects are planned, analysed, and reported. This hands-on, two-day course enables project professionals to design and deploy prompt engineering techniques using ChatGPT, Claude, and other LLM tools to support project planning, risk evaluation, stakeholder reporting, and decision-making.

Through structured labs and a capstone project, learners will master how to leverage AI to generate project documents, perform schedule and risk analyses, summarise progress, and communicate more effectively—all aligned with PMI’s project domains.

LEARNING OUTCOMES:

Day 1 – AI Foundations for Project Planning

Module 1: Introduction to Generative AI & Prompt Engineering

Understand ChatGPT and LLMs. Learn prompt structures using the 5GEARS model.

Hands-on: Compare prompts for scoping vs status update tasks.

Module 2: Prompting for Project Research and Context Setup

Use AI to understand project domains, summarise RFPs, define assumptions, and identify project stakeholders.

Hands-on: Create a project charter prompt workflow.

Module 3: Project Scope and Schedule Planning

Generate WBS outlines, milestone plans, and schedule breakdowns using AI..

Hands-on: Generate Gantt-style prompts, scope baseline summaries, and assumptions logs.

Module 4: Prompt Debugging & Iteration for Project Inputs

Practice improving and correcting prompts for better project deliverables.

Hands-on: Refine prompts for project plans and requirement documentation.

Day 2 – Risk, Reporting and Capstone

Module 5: Prompting for Risk, Issue and Stakeholder Analysis

Automate the generation of risk registers, issue logs, and stakeholder impact summaries.

Hands-on: Use COT/ToT prompts to simulate mitigation plans and stakeholder reactions.

Module 6: Project Reporting & Communication Support

Craft status updates, traffic-light (RAG) reports, executive summaries, and lessons learned reports.

Hands-on: Draft a stakeholder-specific update (e.g. for sponsor vs team).

Module 7: Advanced Prompting for Project Scenarios

Apply Chain-of-Thought (CoT), ReAct, and Tree-of-Thought (ToT) for project change requests, lessons learned sessions, or decision making.

Hands-on: Simulate project decisions using AI-aided analysis.

Module 8: Ethics, Governance, and AI Use in Projects

Discuss bias, hallucinations, and how to manage project confidentiality with AI tools.

Hands-on: Scenario-based discussion

Module 9: Capstone Group Project: Project AI Assistant Pitch

Teams build and present a working AI workflow supporting a project phase (e.g. scoping assistant, meeting summariser, RAG tracker).

Outcome: Group presentations and peer review.

METHODOLOGY: