Get Started for Free →
Learn Programs Library About Us Contact Get Started for Free →
The Complete Edge · ML & GenAI

The Complete Edge.

Three courses, one path. Start from zero Python and finish shipping a production cash-flow forecast that survives a market shock.

Founding offer · GenAI workshop unlocks at launch
3 courses
~12 hours of content
22 modules
2 certs + capstone
Lifetime access
$399$545Save $146
30-day money-back guarantee. No questions asked.
Course 01Beginner
Python Fundamentals
6 modules · 3.5 hours
$99
+
Course 02Intermediate
Applied Machine Learning
7 modules · 2 case studies
$199
+
Course 03AdvancedFounding access
Machine Learning & GenAI for Finance
9 modules · ~5 hours hands-on
$247
The complete path
3 courses · 2 certs + capstone · lifetime access
$399$545
BMO
J.P. Morgan
RBC
TD
BMO
J.P. Morgan
RBC
TD
BMO
J.P. Morgan
RBC
TD
*These banks have used one or more PyFi products to train their employees
The Path

Start at zero. Finish in production.

The path is a deliberate sequence. Build the Python foundation, apply it to real machine-learning problems, then ship a production cash-flow forecast in the GenAI capstone.

Step 01 · Beginner
Python Fundamentals

Build on the Excel skills you already have, see the parallels fast, and put the open-source libraries finance runs on, NumPy and Pandas, to work.

6 modules · 3.5 hours
Step 02 · Intermediate
Applied Machine Learning

Build real ML models on real financial data with scikit-learn. Two full case studies, from raw data to a production model you can explain to your team.

7 modules · 2 case studies
Step 03 · Advanced
Machine Learning & GenAI for Finance

Build a three-layer cash-flow forecast on a real pharma case study: legacy baseline, static ML, dynamic walk-forward retraining, and a guardrailed GenAI loop. This is what production-grade finance ML looks like.

9 modules · ~5 hours hands-on
Two certifications, a capstone, and a portfolio of real work.
Finish with Python fluency, two deployable ML models, and a production cash-flow forecast that survives a market shock.
Outcomes

Everything you can do once you finish the path.

Straight from the course objectives. Python analysis, applied machine learning, and a production GenAI forecast, all on real finance data.

Fundamentals

Analyze financial data with Pandas

Clean, transform, and analyze financial data at a scale and speed a spreadsheet cannot touch.

Fundamentals

Write your own Python tools

Work with Python’s core objects and write reusable functions, loops, and logic.

Applied ML

Ship a bond liquidity regressor

Build it on real data with scikit-learn pipelines, and ship the best of five models.

Applied ML

Build an investor classifier

Evaluate it with confusion matrices, AUROC, and F1 scores, then select the winner.

ML & GenAI

Ship a walk-forward forecast

Retrain as data arrives and recover from a market shock, cutting error 53.8% over the legacy model.

ML & GenAI

Use GenAI with guardrails

Engineer features with AI under schemas, column allowlists, and validation asserts. Governance, not vibes.

What's inside

Three courses. Open each one up.

Expand a course for objectives, curriculum, and a sample lesson.
What you'll be able to do
  • See the direct parallels between the Excel work you already do and Python, so the fundamentals click fast.
  • Get comfortable in a real coding environment: Jupyter notebooks, variables, calculations, and outputs.
  • Work with Python’s core objects (lists, tuples, sets, dictionaries) and write your own functions, loops, and logic.
  • Put NumPy to work for fast, array-based math, aggregation, and randomization.
  • Use Pandas to clean, transform, and analyze financial data at a scale and speed a spreadsheet cannot touch.
  • Tap into the open-source ecosystem: free, professional-grade tools that are a genuine edge over locked-down, paid software.
  • Earn the PyFi certification for your resume and LinkedIn.
Curriculum
01Python BasicsFoundations
02Python ObjectsLists, tuples, sets, dicts
03Custom FunctionsFunctions, loops, logic
04NumPyArray-based math
05PandasClean, filter, analyze
06Certification ExamTimed · all modules
Sample lesson
# Lesson 05.02 · Importing data
import pandas as pd
portfolio = pd.read_csv("holdings.csv")
top_5 = portfolio.nlargest(5, "weight")
Sample05.02 Importing Data
2:43
Sold on its own for$99 · included in bundle
The capstone

A real forecast. A real shock. A real Excel model.

The GenAI capstone is one continuous case study. A weekly cash-flow forecast for a mid-cap pharma company that breaks during a market shock, rebuilt in three layers, then sharpened with a guardrailed GenAI loop.

Case briefing · Week 100–130
RoleFP&A analyst, mid-cap pharma
CompanyVertex Pharmaceuticals (synthetic data)
ChallengeA weekly cash forecast that holds up during disruption
Current toolA blended seasonal model in Excel
ProblemThe Excel model breaks during the COVID-19 shock (Week 112)
Your jobBuild something better, in three layers
Forecast error · MAElower is better
Legacy baseline0.847
Static ML0.612
Dynamic walk-forwardbest0.391
53.8%lower error than the legacy Excel model, through the shock.
01Layer 1

Legacy Baseline

Translate the Excel model into Python. Match every formula. Prove the audit trail.

02Layer 2

Static Machine Learning

Fit a gradient boosting model on operational drivers. Beat the baseline, then watch it drift.

03Layer 3

Dynamic Walk-Forward

Retrain as new data arrives. Recover from the shock. This is the showpiece.

+ a GenAI feature-engineering loop, with finance-grade guardrails
Your tools

No install. No IT department. Open your browser and code.

The capstone runs entirely in the browser, with the real artifacts you would meet on the job.

GitHub Codespaces

Fully configured, browser-based, two minutes to launch. No installs, no IT tickets.

A real Excel artifact

Vertex_Baseline_Model.xlsx — the blended seasonal model you translate, formula by formula.

Synthetic dataset

vertex_pharma_cash_synthetic.csv — 19 columns of weekly cash, operational drivers, and shock flags.

Pre-built src/ package

Reporting, charting, and PDF plumbing already written. You focus on the ML, not the boilerplate.

Certification

Two certifications and a capstone. One signal to employers.

Finish each course and pass its timed exam to earn a PyFi Certification. The GenAI capstone adds a production forecast you can show, not just describe. Proof you can put Python and machine learning to work from day one.

Built on algorithms used to advise
HormelHPCardinal HealthGapAmerisourceBergenMcDonald'sAmerican WaterMacy's

The Applied ML case studies are modeled on real corporate advisory work. Code is altered to protect client IP.

PyFiCertificate of Completion
This certifies proficiency in
Python Fundamentals
Zach Washam
Head of Instruction · PyFi
PyFi Certified
PyFiCertificate of Completion
This certifies proficiency in
Applied Machine Learning
Zach Washam
Head of Instruction · PyFi
PyFi Certified
PyFiCapstone Project
Production capstone in
ML & GenAI for Finance
Umut Sagir
Head of Programming · PyFi
Unlocks at launch
Your instructors

Two practitioners. The full path, taught end to end.

Zach Washam
Zach Washam
Founder
Teaches Python Fundamentals · Applied Machine Learning

Zach Washam
Ex Wells Fargo

Zach founded PyFi (originally Machine Learning Edge) in 2018 after a career at Wells Fargo Securities. While working as an analyst on the debt syndication desk, he taught himself Python and built the firm’s first machine learning algorithm for investment banking, using predictive modelling to improve decision-making in capital markets.

He submitted two algorithms for patent protection and won Wells Fargo’s 2018 Local Sphere Innovation Award. Zach’s original research, including the efficient frontier framework for mapping Python against competing finance tools, remains foundational to PyFi’s published work. His courses have been delivered to thousands of finance professionals at institutions including J.P. Morgan, Royal Bank of Canada, Bank of Montreal, and TD Bank.

Ex Wells Fargo Securities
Built WFS’s first ML algorithm for investment banking
2018 Local Sphere Innovation Award
Taught thousands of finance professionals
Is this for you?

This path is for you if...

  • You want the full journey from zero Python to a production forecasting model.
  • You use Excel daily and want to rebuild your models in Python, formula by formula.
  • You want to build and ship ML, not just understand it in theory.
  • You are ready for an advanced, hands-on capstone on real-world finance data.

The path is not for you if...

Enroll

The Complete Edge

4.9out of 5
$399.00 USD$545.00 USD27% OFF
Get the bundle

Join over 10,000 professionals in the finance function from analysts, associates, VPs of investments, and CFOs, including top banks like JP Morgan, TD Bank, Bank of Montreal, and Royal Bank of Canada who have used PyFi to keep their skills ready for the future of finance.

What's included
Python Fundamentals course + certificate
Applied Machine Learning course + certificate
Machine Learning & GenAI for Finance
Founding access, unlocks at launch
Two PyFi certifications + the GenAI capstone
Lifetime access + instructor support
30-day money-back guarantee
30-day guarantee Secure checkout

Already own a course? Email support@pyfi.com and we'll credit it toward the bundle.

Questions

Common questions about the path.

Yes. You get Python Fundamentals and Applied Machine Learning immediately, plus founding access to Machine Learning & GenAI for Finance the moment it launches, locked in at today’s price.