Claude AI in Project Planning, Scheduling & Cost Controlling

What you'll learn

• Write engineering-grade prompts that produce usable, correctly structured controls output first time
• Give Claude your data properly, iterate on weak answers and build a reusable prompt library
• Draft and stress-test scope, WBS and estimates — and produce a defensible basis of estimate
• Turn scope into activities, interrogate schedule logic and float, and write clear schedule narratives
• Model budgets, cash flow and S-curves, build risk registers and frame qualitative and quantitative risk
• Run full Earned Value analysis (CV, SV, CPI, SPI) and forecast EAC, ETC and TCPI with honest commentary
• Produce faster status reports, executive summaries, emails, minutes and contract/change correspondence
• Review long documents and contracts, and capture lessons learned at close-out
• Build simple AI mini-tools and connect Claude to your P6/MSP/Excel/Drive data
• Apply AI governance, quality control and a human-in-the-loop checklist so AI use stays safe and accountable

About this course

A hands-on course built specifically for the project controls workflow. Across 11 sections and 64 lessons you run the whole cycle on a realistic infrastructure project: engineering-grade prompting and the RACE framework, scope and WBS, estimating, scheduling and narratives, cost, cash flow and risk, Earned Value and forecasting, reporting and correspondence, then automation and AI governance. Every lesson gives the controls principle first, then how to get Claude to do it well, then how to verify the output before you rely on it — augmentation, not automation.

Requirements

• No AI or prompt engineering experience required
• Basic understanding of project management concepts is helpful but not mandatory

Who this course is for

• Planning, cost and project controls engineers, planners and schedulers
• Project managers and assistant project managers
• Civil, structural, mechanical and MEP engineers
• Contracts and commercial managers
• Anyone who wants to use AI to improve productivity and documentation quality