Class of ML
Build Real
ML Systems.
Go beyond tutorials. Work on real Pakistani datasets, build real pipelines, ship real models. This is not a course — it is a builder program.
The Program
What You'll Do
Real Datasets
Work with actual Pakistani data: air quality indices, court case records, agricultural yields. No toy datasets.
Build Pipeline
Design end-to-end ML pipelines from data collection to model deployment. Hand-draw your architecture, explain your decisions.
Ship Models
Deploy working models with real APIs. Your output is not a notebook — it is a production-ready system.
How You Get In
Your Selection Process
Application
Free · 10 min
Basic details + why you want to build ML systems. No GPA, no resume, no prior experience required.
Screening
Free · 30 min
Conceptual ML understanding. No code required. Diagnose training/validation gaps on Pakistani datasets.
Assessment
Rs. 1,000 · 48 hours
Predict whether tomorrow’s Lahore AQI will cross 200. Submit a clean repo, a hand-drawn pipeline diagram, and a 3-minute voice note explaining your approach.
The Output
What a Class of ML
output looks like
48-Hour Assessment Build
Lahore AQI Predictor
Epoch 12/15 — loss: 0.0342 — val_loss: 0.0289 — val_accuracy: 0.891
Epoch 13/15 — loss: 0.0318 — val_loss: 0.0275 — val_accuracy: 0.897
Epoch 14/15 — loss: 0.0301 — val_loss: 0.0268 — val_accuracy: 0.903
Best model saved: lahore_aqi_v2.pt (val_acc: 0.903)Hand-Drawn Pipeline