Coding problems
33 Python problems (NumPy, Python, or PyTorch in the language dropdown) and 27 SQL warehouse problems. Filter by role — every role’s questions live on this list. Easy problems are free; medium and hard need Pro.
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| Status | Problem | Language | Difficulty | Track |
|---|---|---|---|---|
| 1. Mean ~5 min · Google, Meta | Python | easy | Python Foundations | |
| 2. Mean squared error ~8 min · Google, OpenAIPro | Python | medium | ML metrics | |
| 3. Mean absolute error ~6 min · Amazon, GooglePro | Python | medium | ML metrics | |
| 4. ReLU ~5 min · Google, Meta | Python | easy | Python Foundations | |
| 5. Dot product ~6 min · Google, NVIDIAPro | Python | medium | Python Foundations | |
| 6. Argmax ~5 min · Meta, ApplePro | Python | medium | — | |
| 7. Clip ~6 min · Stripe, GooglePro | Python | medium | Python Foundations | |
| 8. Flatten ~5 min · Amazon, NetflixPro | Python | medium | Python Foundations | |
| 9. Min-max normalize ~10 min · Google, DatabricksPro | Python | hard | — | |
| 10. Softmax ~12 min · OpenAI, GooglePro | Python | hard | Tensors & ranking | |
| 11. Mean ignoring NaN ~8 min · Tesla, GooglePro | Python | medium | Stats the analyst pad asks | |
| 12. Population variance ~8 min · Meta, Two SigmaPro | Python | medium | Stats the analyst pad asks | |
| 13. Population standard deviation ~8 min · Jane Street, GooglePro | Python | medium | Stats the analyst pad asks | |
| 14. Median ~8 min · Amazon, BloombergPro | Python | medium | Stats the analyst pad asks | |
| 15. Cumulative sum ~6 min · Stripe, UberPro | Python | medium | — | |
| 16. Cosine similarity ~12 min · OpenAI, GooglePro | Python | hard | Tensors & ranking | |
| 17. Moving average ~10 min · Bloomberg, QuantCoPro | Python | hard | Stats the analyst pad asks | |
| 18. Unique sorted ~6 min · Apple, AmazonPro | Python | medium | — | |
| 19. Count a value ~5 min · Meta, NetflixPro | Python | medium | Python Foundations | |
| 20. Weighted mean ~8 min · Airbnb, GooglePro | Python | medium | Stats the analyst pad asks | |
| 21. R-squared ~12 min · Databricks, GooglePro | Python | hard | ML metrics | |
| 22. Manhattan distance ~6 min · Uber, LyftPro | Python | medium | — | |
| 23. Log-softmax ~12 min · OpenAI, AnthropicPro | Python | hard | Tensors & ranking | |
| 24. Pearson correlation ~14 min · Two Sigma, CitadelPro | Python | hard | Tensors & ranking | |
| 25. Binary cross-entropy ~14 min · OpenAI, AnthropicPro | Python | hard | ML metrics | |
| 26. Precision ~12 min · Meta, GooglePro | Python | hard | ML metrics | |
| 27. Top-k indices ~12 min · Google, NVIDIAPro | Python | hard | Tensors & ranking | |
| 28. Z-score ~12 min · Jane Street, CitadelPro | Python | hard | Stats the analyst pad asks | |
| 29. Shannon entropy ~12 min · DeepMind, GooglePro | Python | hard | Tensors & ranking | |
| 30. Recall ~12 min · Meta, GooglePro | Python | hard | ML metrics | |
| 31. F1 score ~14 min · OpenAI, AnthropicPro | Python | hard | ML metrics | |
| 32. KL divergence ~14 min · DeepMind, Two SigmaPro | Python | hard | Tensors & ranking | |
| 33. Huber loss ~14 min · NVIDIA, Jane StreetPro | Python | hard | Tensors & ranking | |
| 34. Completed revenue by country ~10 min · Stripe, Shopify, SquarePro | SQL | medium | SQL Foundations | |
| 35. Top products by units sold ~10 min · Amazon, Walmart, InstacartPro | SQL | medium | SQL Foundations | |
| 36. Who reports to Ben ~6 min · Google, Meta, MicrosoftPro | SQL | medium | SQL Foundations | |
| 37. Orders with more than one line ~8 min · Instacart, DoorDash, Shopify | SQL | easy | SQL Foundations | |
| 38. Event funnel by stage ~10 min · Meta, Snap, PinterestPro | SQL | medium | SQL Foundations | |
| 39. Orders with no payment ~10 min · PayPal, Capital One, StripePro | SQL | medium | Warehouse SQL Core | |
| 40. Cancel rate by country ~12 min · Uber, DoorDash, LyftPro | SQL | medium | Warehouse SQL Core | |
| 41. Daily completed revenue ~10 min · Meta, Netflix, SpotifyPro | SQL | medium | Warehouse SQL Core | |
| 42. Customer lifetime summary ~15 min · Airbnb, Booking, ExpediaPro | SQL | medium | Warehouse SQL Core | |
| 43. Running total of daily revenue ~12 min · Stripe, Airbnb, BookingPro | SQL | medium | Windows & Time Series | |
| 44. Seven-day moving average ~14 min · Netflix, Spotify, UberPro | SQL | hard | Windows & Time Series | |
| 45. Day-over-day revenue growth ~14 min · Meta, Uber, LyftPro | SQL | hard | Windows & Time Series | |
| 46. Revenue share by country ~12 min · Amazon, Shopify, MetaPro | SQL | medium | Windows & Time Series | |
| 47. Latest order per customer ~12 min · Shopify, Square, InstacartPro | SQL | medium | Ranking & Dedup | |
| 48. Top two products per category ~14 min · Amazon, Walmart, TargetPro | SQL | hard | Ranking & Dedup | |
| 49. Salaries above the department average ~14 min · Google, Microsoft, BloombergPro | SQL | hard | Ranking & Dedup | |
| 50. Reconcile orders against payments ~14 min · Stripe, Capital One, WisePro | SQL | hard | Data Quality & Hard SQL | |
| 51. Traffic source from JSON payload ~12 min · Snowflake, Databricks, AirbnbPro | SQL | medium | Data Quality & Hard SQL | |
| 52. Payment method mix by day ~12 min · Stripe, PayPal, AdyenPro | SQL | medium | Data Quality & Hard SQL | |
| 53. Median completed order amount ~18 min · Capital One, JPMorgan, RobinhoodPro | SQL | hard | Data Quality & Hard SQL | |
| 54. Sessionize events (30-minute gap) ~20 min · Netflix, Spotify, AirbnbPro | SQL | hard | Data Quality & Hard SQL | |
| 55. Customers who cancelled and completed ~16 min · Stripe, Adyen, Checkout.comPro | SQL | hard | Data Quality & Hard SQL | |
| 56. Customers who bought every category ~18 min · Amazon, Instacart, WalmartPro | SQL | hard | Data Quality & Hard SQL | |
| 57. Second order within seven days ~18 min · Shopify, DoorDash, UberPro | SQL | hard | Data Quality & Hard SQL | |
| 58. Hours from order to settlement ~18 min · Stripe, Adyen, PayPalPro | SQL | hard | Data Quality & Hard SQL | |
| 59. First-touch traffic source ~18 min · Airbnb, Shopify, MetaPro | SQL | hard | Data Quality & Hard SQL | |
| 60. Customers above average order volume ~16 min · Amazon, DoorDash, UberPro | SQL | hard | Data Quality & Hard SQL |
No problems match those filters.