Business Free course · Certificate included
Project Controls in the AI Era
Plan, measure, forecast and control projects with earned value, Monte Carlo risk analysis and governed AI
- Advanced
- 9 h 1 min
- 22 lessons in 6 modules
- 3 h 2 min of video lectures
- Updated Sep 2026
About this course
A practitioner-level course on the full project controls cycle: work breakdown structures, critical path scheduling, resource levelling, cost engineering and estimating, cost control, earned value management (EV, PV, AC, CPI, SPI), forecasting with EAC, ETC, TCPI and earned schedule, cash flow, risk registers and Monte Carlo schedule risk analysis, change control, and reporting that drives decisions. Every lesson has a narrated lecture with two worked examples and a step-by-step walkthrough, plus hands-on Excel formulas, Python (pandas and NumPy) notebooks, report templates and prompt templates. The final module shows how AI can assist forecasting, anomaly detection and reporting, and how to govern it with human review, audit trails and data quality controls.
Preparing for PCI AI's PCL-AI (Project Controls Leader) credential? This course builds the foundations; see pciai.org for official exam details. Certuvo (certuvo.com) offers exam preparation for PCL-AI, PFL-AI and PML-AI. This course is independent and is not official PCI AI content.
Tools you’ll use
- Primavera P6
- Microsoft Project
- Microsoft Excel
- Power BI
- Python
- pandas
- NumPy
- Jupyter
- @RISK
- Safran Risk
- Deltek Acumen Risk
- Microsoft 365 Copilot
Skills
- Project controls
- Earned value management
- Scheduling (CPM)
- Cost engineering
- Forecasting
- Schedule risk analysis
- Python for project controls
- AI governance
What you’ll be able to do
- Build a deliverable-based WBS, control accounts and an integrated performance measurement baseline
- Calculate critical path, float and resource-levelled schedules from quantities and productivity
- Calculate and interpret CV, SV, CPI, SPI, EAC, ETC, VAC, TCPI and earned schedule in Excel and Python
- Produce defensible cost and schedule forecasts and challenge optimistic ones
- Run a risk register, build and interpret a Monte Carlo schedule risk model (P50/P80) and operate change control
- Design decision-focused reports and dashboards on reconciled, governed data
- Apply AI to forecasting, anomaly detection and reporting with risk-tiered human review and audit trails
Curriculum
Syllabus
- Modules
- 6
- Lessons
- 22
- Reading time
- 5 h
- Assessment questions
- 25
What project controls is, how the control cycle works, and how scope, schedule and cost baselines are built from a solid WBS and critical path.
- What project controls really isVideo lecture, 9′12 min
- Work breakdown structures and the integrated baselineVideo lecture, 8′14 min
- Scheduling and the critical pathVideo lecture, 9′Video · 16 min
- Resource loading, levelling and schedule maintenanceVideo lecture, 8′14 min
Build a cost baseline, manage commitments and actuals, and use earned value management to measure cost and schedule performance objectively.
- Cost engineering: estimating methods and estimate classesVideo lecture, 8′15 min
- Budgets, commitments and cost controlVideo lecture, 8′13 min
- Earned value management: the core metricsVideo lecture, 9′16 min
- Measuring progress objectivelyVideo lecture, 8′13 min
Turn performance data into honest forecasts using EAC/ETC methods, TCPI, earned schedule and structured forecast reviews.
- EAC and ETC: forecasting the final costVideo lecture, 9′15 min
- Schedule forecasting and earned scheduleVideo lecture, 8′14 min
- Running forecast reviews that change decisionsVideo lecture, 8′12 min
- Cash flow forecasting and the link to project financeVideo lecture, 8′13 min
Write actionable risk registers, build and interpret Monte Carlo schedule risk models in Python and Excel, and operate change control that keeps the baseline honest.
- Risk registers that drive actionVideo lecture, 9′13 min
- Quantitative risk analysis and Monte Carlo simulationVideo lecture, 8′Video · 16 min
- Lab: an EVM and Monte Carlo notebook in PythonVideo lecture, 9′25 min
- Change control and baseline managementVideo lecture, 8′12 min
Design reports and dashboards that drive decisions, and build the data foundations that make controls, and AI, trustworthy.
- Reports and dashboards that drive decisionsVideo lecture, 8′13 min
- Data foundations: integration, quality and toolsVideo lecture, 8′13 min
- Performance analysis in practice: a full monthly cycleVideo lecture, 8′14 min
Apply AI to forecasting, risk and reporting responsibly, with human review, audit trails, data quality and a practical adoption roadmap.
- Where AI adds value in project controlsVideo lecture, 8′14 min
- Governing AI: human review, audit trails and data qualityVideo lecture, 8′15 min
- An AI adoption roadmap for controls teamsVideo lecture, 8′12 min
- Final assessment
Your certificate
Finish with a credential anyone can check
Earn the Project Controls in the AI Era badge: The holder has demonstrated applied knowledge of project controls: WBS and baselines, critical path scheduling, cost engineering, earned value management, EAC/ETC and earned schedule forecasting, risk registers and Monte Carlo interpretation, change control, decision-focused reporting and the governed use of AI with human review and audit trails.
Completed all lessons and scored ≥ 80% on the final assessment.
- A public verification page
- A PDF certificate to download
- An Open Badge you can share
- One click to your LinkedIn profile
Final assessment
- 25questions drawn from a larger pool
- 45 mintime limit
- 80%pass mark
- 3attempts per 24 hours
Start learning today. It’s free.
Every lesson is free to read. A free account saves your progress, unlocks the final assessment and issues your certificate.