This course contains the use of artificial intelligence. Stop watching AI demos. Start doing the work. Most “AI for accounting” courses show you prompts on the instructor’s screen and hand you nothing to practice on. This course is different: you work a single, realistic, deliberately-flawed dataset for a fictional SaaS company — NovaBridge, Inc. — across the entire accounting cycle, and you catch what the AI (and the data) got wrong.
You’ll use the tools you actually have access to — ChatGPT, Claude, and Microsoft Copilot (including Excel Copilot) — as your daily driver, then see how enterprise finance teams run the same jobs on specialized platforms like Trullion, Bill, HighRadius, Ramp, Vic, BlackLine, FloQast, Datarails, and MindBridge.
What makes this practical:
- One recurring dataset — a general ledger, trial balance, AR aging, invoice batch, expense export, customer contract, bank feed, and actuals-vs-budget, all seeded with realistic errors to find.
- A downloadable Lab Kit for every lecture — the artifact, a copy-paste prompt pack, a step-by-step exercise, an answer key, and a validation checklist.
- Guardrails baked into every lab — never paste client data into public models, keep a human sign-off, recompute every figure, and preserve an audit trail. This is accounting-grade AI, not clever prompting.
- A capstone — run NovaBridge’s full month-end close end-to-end with AI.
