Course materials, organized by week. Everything posted here is also available inside Canvas; this page is a direct way to browse it. Weeks are added as the term goes. The grayed-out ones below are not posted yet, so the whole term is visible from the start.
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Week 1 — Foundations
Analytics in accounting, AI as method. Build a reusable profile, then find out what a model does with it.
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Week 2 — Working with AI: Context, Prompting, and DeterminismNot yet posted
Excel is deterministic; an LLM is not. A careful specification is what makes a non-deterministic tool reliable.
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Week 3 — Data Sources: AR, Aging, and Cash Application (SQL)Not yet posted
Build the AR aging report in Excel, then recreate the same headline numbers in SQL on the in-browser SQL Workbench.
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Week 4 — Excel Fundamentals, Power Query, and FSA SetupNot yet posted
The Excel formula toolkit until it is automatic, then ingest the real Compustat data with Power Query and winsorize it. The workbook you build starts Project 1.
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Week 5 — Excel Analytics and VisualizationNot yet posted
The chart is the deliverable. Age Summit Gear's receivables by days past due, build the six charts that answer the controller, and read each one honestly. Project 1 is due this week.
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Week 6 — Exploratory Data Analysis: Read the Distribution, Then Tell the StoryNot yet posted
Read the shape of your data before summarizing it. Choose mean or median for a reason, and turn the analysis into a story a decision-maker can act on.
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Week 7 — Python and pandas for Accounting DataNot yet posted
Every Excel move has a Python equivalent. Rebuild the Summit Gear receivables in pandas, where a function is a named formula, a loop is a running total, and a mask is an IF. Once it is code, it re-runs next quarter for free.
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Week 8 — Unstructured Data: Text, Images, and ExtractionNot yet posted
Accounting evidence rarely arrives as a tidy table. Pull structured data out of contracts, invoices, and scanned documents, and verify the extraction before you rely on it. Project 2 is due this week.
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Week 9 — Analytical ModelingNot yet posted
Frame the question before fitting anything. What makes a model useful for an accounting decision, which baseline it has to beat, and how you will know when it is wrong.
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Week 10 — Supervised Learning: RegressionNot yet posted
Fit OLS on accounting data and read what each coefficient is really telling you. Predict the number, then defend the prediction.
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Week 11 — Supervised Learning: ClassificationNot yet posted
Predict the yes/no: which invoices go delinquent, which transactions deserve review. Thresholds, error costs, and what a confusion matrix actually says. Project 3 is due this week.
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Week 12 — Unsupervised LearningNot yet posted
No labels this time. Cluster transactions and customers, screen the outliers, and decide what a segment means before acting on it. The Project 4 proposal is due this week.
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Week 13 — Automation, Agents, and Tool CallsNot yet posted
Turn the term's methods into a pipeline that re-runs itself. Agents, tool calls, and the checks that keep an automated process trustworthy.
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Week 14 — Analytics in PracticeNot yet posted
Guest speakers and industry tooling. No new lab or homework, so the capstone has room.
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Week 15 — Capstone Work WeekNot yet posted
No new material. The week belongs to Project 4, due Friday, December 11.