$2325

4 Seats

The class will use Excel™ for hands-on instruction and includes lecture, demonstration, and guided discussion.

What you’ll learn

  Statistics for fire and EMS — without the difficult math
  Using AI for data cleanup and data engineering: CAD, NFIRS, NERIS, and RMS data
  Using AI for analysis: response times, turnout, travel, ERF, unit reliability
  Using AI for mapping: incidents, travel-time, station coverage, risk — without an ArcGIS license
  Excel for operations data: pivot tables, filtering, sorting, summarizing
  Percentiles, NFPA compliance, and what an honest response-time report looks like
  Effective Response Force, unit concentration, and order of arrival
  Identifying and handling outliers consistently — not just deleting them
  Setting performance objectives that are realistic and defensible
  Data quality: what to fix before any analysis, AI-assisted or otherwise
  Tables and graphs that communicate — and the ones that don’t
  Small-data considerations: when your numbers are too thin to support your claim
  Correlation: reading relationships between variables without overreaching
  Recognizing AI failure modes — the ones that will burn you if you don’t know to look for them