◆ FIRST RESULTS
The first students through the program.
We're early, and I'd rather show you real people by name than a wall of stock quotes. More stories will land here as students finish — posted with their permission only.
Pradeep Saini
Data Analyst at Chosen Store
Placed at Chosen Store
Non-tech background, BA in 2022, then a four-year gap. Learnt data from scratch in the program and landed a full-time role.
Akshobya
Data Analyst track
Earned three offers plus an internship
Had multiple offers on the table and chose the internship — the path he actually wanted.
THE LEVEL OF REVIEW YOU GET · EXAMPLE: DATA ANALYST TRACK
INSIDE THE PROGRAM
A peek at the dataset.
A realistic e-commerce schema with messy real-world data, not a toy CSV. You'll write SQL against tables like these from day one.
orders7 columns
idcustomer_idproduct_idqtytotal_inrstatuscreated_at
customers6 columns
idemailsignup_sourcecitylifetime_value_inrfirst_order_at
products6 columns
idnamecategoryprice_inrstocksupplier_id
sessions6 columns
iduser_iddevicesourcestarted_atduration_sec
Illustrative schema - the real one has more tables and 18 months of data.
WHAT A REVIEW LOOKS LIKE
Direct, specific, actionable.
Every submission gets a written review like this within 24 hours. No rubrics, no rubber-stamps - just what to fix and why.
AS
Anuj Saini
Reviewing · Week 8 ML model
The churn model runs and the notebook is clean - good. Two things before this is portfolio-ready:
1. You're leading with 91% accuracy, but churn is ~8% of the base, so a "nobody churns" baseline already scores 92%. Report precision/recall + PR-AUC instead, and tie the threshold to the retention-campaign cost - that's the number a stakeholder actually cares about.
2. Your Lambda job pulls the full table on every run. Add an incremental filter on `updated_at` so the scheduled pipeline stays cheap as the data grows.
Re-run with the honest metrics and a short "what I'd do with more time" note, then tag me when it's up.
Illustrative excerpt. Real reviews are tailored to your specific submission.
Anuj has sat on hiring panels at 5 product companies
250+ data resumes reviewed across 6+ years in industry
Not sure it's the right fit? Drop your details first — you'll get a real reply from Anuj, not a sales team.