Certified
Self-directed project
Machine Learning for Automotive
AI / ML · June 2026
92/ 100
A ProoV case study · educational project, not employment
A verified, self-directed industry project — completed and passed a real industry rubric at 92/100 on ProoV.
Graded against
- Exploratory Data Analysis20%
- Feature Engineering25%
- Model Building & Evaluation35%
- Business Communication20%
Passed · pass mark 60/100
What stood out6
- Compared Linear Regression and Random Forest using R², MAE, and RMSE with clear performance gains quantified.
- Identified and communicated the top pricing drivers, including mpg, car_age, and engineSize.
- Provided a practical CPO recommendation to adopt the tuned Random Forest and apply manual review for outliers.
- Included a brand-level pricing comparison example (VW Golf vs Audi A4) to translate model output into business terms.
- Exploratory Data Analysis
- Feature Engineering
The work I submitted10 tasks
5 tasks · 6 lines · 5 written answers · 183 words
- VW Sprint1 Complete56 characters
- VW Sprint2 Complete61 characters
- VW Sprint3 Complete59 characters
- VW Business Insights1.7k characters
- Jupyterlite Code2 lines
- VW Sprint1 Complete1 word
- VW Sprint2 Complete1 word
- VW Sprint3 Complete1 word
- VW Business Insights179 words
- Jupyterlite Code1 word
Summarised on purpose — the submitted code and writing stay private so this page cannot be reused as an answer key. The full submission sits behind the verified certificate.