FPandA
📊 FP&A + Automation – Full Course Track
Welcome to the FP&A track at QuantML — where monthly reporting isn’t a soul-sucking copy-paste ritual, and forecasting doesn’t involve guesswork, Excel crashes, or three different files named FINAL_FINAL_v3.xlsx.
This course teaches you how to automate real FP&A tasks using:
Python for data wrangling & reports
Machine learning for smarter forecasting
GPT for commentary, analysis, and presentations
Streamlit for building tools your team will actually use
🧠 What You’ll Learn
You’ll go from:
“Why does this variance report take two days to make?”
to
“I built a self-updating reporting system with GPT insights and push-button commentary.”
You’ll learn how to:
Automate P&L variance reports
Clean and merge ugly ERP dumps
Forecast revenue, COGS, and margins with ML
Build auto-updating dashboards
Generate decks and insights using GPT
🧱 How This Track Works
You get real FP&A use cases, with:
✅ Python code for each workflow
📊 Real (anonymized) data examples
📈 Monthly reporting templates
💬 GPT prompt packs for finance commentary
🎥 Walkthroughs you can watch while ignoring meetings
🔥 Complete Module Breakdown
✅ Module 0 – Data Wrangling for FP&A
Goal: Prepare monthly financial data for automation
Outcome: Clean, merged, analysis-ready datasets
Lessons:
Reading messy Excel dumps from ERP systems
Cleaning multi-sheet exports
Creating reporting-ready tables from GL data
Standardizing business unit/cost center names
Merging actuals, budget, forecast, and PY into one frame
✅ Module 1 – Variance Reporting Automation
Goal: Create automated, refreshable variance reports
Outcome: Reports that explain themselves while you scroll LinkedIn
Lessons:
Calculating absolute and % variance (MoM, YoY, vs Budget)
Highlighting materiality thresholds
Exporting Excel reports with highlights using
openpyxlCreating summary tables by cost center, BU, or account
Automating commentary generation with GPT
✅ Module 2 – Forecasting & Rolling Forecasts
Goal: Predict next month’s numbers with data, not vibes
Outcome: Smarter forecasts that actually adjust over time
Lessons:
Rolling 12-month forecast builder
Using linear regression to project revenue/COGS
ML forecasting models for seasonal data
Integrating business assumptions with ML
GPT for forecast explanation and business impact write-up
✅ Module 3 – PowerPoint & Report Deck Generation
Goal: Build decks that update themselves
Outcome: No more late-night deck edits because “Ops changed the numbers again”
Lessons:
Writing PowerPoint files from Python
Feeding in numbers + GPT commentary
Auto-formatting charts, tables, and titles
Exporting PDF decks from your script
Automating deck distribution via email (bonus)
✅ Module 4 – Streamlit Dashboards for Finance
Goal: Build internal dashboards for live reviews
Outcome: Impress everyone. Terrify the intern.
Lessons:
Building dashboards with Streamlit
Filters by BU, month, scenario (actual/budget/forecast)
Live commentary from GPT based on selections
Exporting to Excel/PDF from the app
Secure sharing (Streamlit Cloud, HuggingFace Spaces)
✅ Module 5 – Monthly Close + BI Integration
Goal: Connect to BI tools and create a smooth close process
Outcome: Reports that update without human drama
Lessons:
Exporting data from Tableau / Power BI into Python
Using Excel connector dumps (Oracle, SAP, NetSuite)
Auto-validating monthly numbers
Generating audit-ready logs of changes
GPT-generated “month-end summary” reports
✅ Module 6 – Final Projects
Goal: Build tools that save 10+ hours/month
Outcome: Job security, or at least internal fame
Project Ideas:
Monthly P&L Reporting App (Streamlit + GPT)
Automated Forecasting Tool (Python + ML)
FP&A Review Deck Generator (Excel → GPT → PowerPoint)
Scenario Summary Bot (“How will this scenario impact margins?”)
Email Update Engine (“Send this update to all BUs at month-end”)
🎯 Who This Is For
This is for anyone in or near FP&A, including:
FP&A managers drowning in reporting cycles
Finance controllers managing budgets and forecasts
Analysts and MBAs who want to work smarter
Anyone whose job involves copying numbers into decks
Sad people who manually color-code Excel reports
🧠 Tools You’ll Use
Python (
pandas,openpyxl,matplotlib,scikit-learn)GPT via OpenAI API
Streamlit for dashboards
PowerPoint automation with
python-pptxExcel connectors and BI exports
👇 Get Started
This track is where real finance automation begins. If you’ve ever thought “There has to be a better way to do this,” — well, here it is.
👉 Subscribe to QuantML to get full access
Or keep doing month-end the old way. Enjoy your spreadsheet-induced migraines.