Overview
What this challenge is about.
Churn-Prediction Model for a B2B Vertical SaaS. Intermediate challenge in code. Writing production code that solves real engineering problems, earn a blockch...
The Brief
What you'll do, and what you'll demonstrate.
Build a churn-prediction model that beats CS gut-feel on precision-at-top-200 and is paired with an actionable playbook.
This is not a coding exercise. It is the work a software engineer does between a Jira ticket and a merged PR. That distinction matters to every hiring manager who has seen candidates solve LeetCode problems and none who have shipped production code under real constraints.
When you finish, you will have something most graduates do not: a real-world deliverable, verified by Ewance, that you can show to a hiring manager and say "I did this. Here is the proof."
Earning criteria — what you'll demonstrate
- Apply supervised learning to a real churn-prediction task with proper splits
- Compare baseline vs gradient-boosted models on business-relevant metrics
- Use SHAP to translate model behavior into intervention guidance
- Pair ML output with operational playbook for measurable impact
Program Fit
Where this fits in your program.
Sharpens the same skills your degree expects you to demonstrate.
Machine Learning (CS Elective)
Master · General Studies
Strong alignment
This challenge maps to Machine Learning (CS Elective) at the Master level. It sharpens the same practical skills your coursework expects — but in a real industry context with actual constraints and deliverables.
Skills
Skills you'll demonstrate.
Each one shows up on your verified credential.
- Supervised Learning
Apply supervised learning to solve real industry problems and demonstrate production-level capability.
- Python Programming
Apply python programming to solve real industry problems and demonstrate production-level capability.
- Ml Applications
Apply ml applications to solve real industry problems and demonstrate production-level capability.
- Model Evaluation
Apply model evaluation to solve real industry problems and demonstrate production-level capability.
- Feature Engineering
Apply feature engineering to solve real industry problems and demonstrate production-level capability.
- Business Analytics
Apply business analytics to solve real industry problems and demonstrate production-level capability.
Careers
Career paths this challenge builds toward
Completing this challenge demonstrates skills that transfer directly to these roles:
Product Manager
PMs on retention products need this end-to-end ML-to-playbook fluency to scope features that actually move net-revenue retention.
This challenge sharpens
- business-analytics
- ml-applications
- model-evaluation