A practical, notebook-based course that teaches you to replace your most painful Excel workflows with clean, automated Python — using real finance examples.
Currently in development · Register to hear when it launches
Most Python courses teach you to classify iris flowers and predict house prices. This one teaches you to build DCF models, automate monthly P&L reports, and replace VLOOKUPs — because that's what you actually do at work.
run_monthly_report()Every notebook builds something you'd actually use at work. Here's a slice from Module 4 — a DCF sensitivity table that used to take an afternoon in Excel.
No fluff. No toy examples. Every module is a Jupyter notebook with working code and a real financial deliverable at the end.
The honest Excel vs Python comparison. Environment setup (Colab or local). Load a P&L from Excel, calculate margins, produce a dual-axis chart — in 20 lines of code.
VLOOKUP → merge(). SUMIF → groupby(). Pivot tables, date handling, month-over-month growth, rolling averages, and conditional logic. Every function you use daily, translated.
Build a full 3-year income statement. All assumptions in one place. Sensitivity tables (no Excel Data Tables). Bear / base / bull scenario analysis with a single function call.
5-year FCF projection, WACC calculation, Gordon Growth terminal value, equity bridge to implied share price. Sensitivity heatmap: price vs WACC and terminal growth rate.
The three-layer model structure (inputs / engine / outputs). Validation functions that catch errors automatically. Git version control — no more filename suffixes. Reusable templates across companies.
The payoff module. Build a pipeline that ingests raw data, runs the model, validates outputs, generates a formatted Excel report, and produces a dashboard chart. One command. Every month.
None. The course assumes you're comfortable in Excel but have never written Python. Module 1 starts from absolute zero and every concept is explained from the Excel equivalent you already know.
No. Every notebook runs in Google Colab — free, in your browser, with no installation. All you need is a Google account. If you prefer a local setup, Module 1 includes instructions for Anaconda.
Each module takes 1–2 hours to work through properly. The full course is designed to be completed over 6–8 weekends at a comfortable pace. You can also dip in and out — each notebook is self-contained.
Finance professionals don't have time to watch a 4-hour video course. Notebooks are denser, faster to work through, and you can run the code yourself as you go. They're also easy to adapt to your own models immediately.
Yes — because it runs in Google Colab (a browser tab), it doesn't require any software installation that might be blocked by IT. You just need internet access and a personal Google account.
Every notebook is fully self-contained and runs top-to-bottom without errors. If you hit an issue, email hello@codifyit.co.uk and you'll get a reply within 48 hours.
The course is being finalised now. Register your interest and we'll email you the moment it's ready — no spam, just a single note when it's available.
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