Browse by Topic
167 questions across 11 topics — probability, ML, SQL, Python, business cases, and more. Every question has a full explanation. No fluff.
Getting Started
Roadmap, company expectations, storytelling with data, and confidence building.
Probability
Bayes' theorem, distributions, conditional probability, and expected value problems.
Python Coding
LeetCode-style problems + pandas, NumPy, and data manipulation tasks.
Descriptive Stats
Mean, median, variance, outliers, distributions, and data summarization.
Business Case Studies
Product sense, metric design, and feature impact analysis — Swiggy, Zomato, and more.
ML Breadth
Supervised, unsupervised, regularization, feature engineering, and model selection.
Inferential Stats
A/B testing, hypothesis testing, p-values, confidence intervals, and experiment design.
ML Depth
From-scratch derivations — logistic regression, gradient descent, backprop, transformers.
SQL
Real company problems — Meta, Google, Amazon, Netflix, Shopify, LinkedIn.
Take-Home Assignments
Full Jupyter notebook exercises used in real hiring pipelines.
ML System Design
End-to-end ML system design: recommendation engines, duplicate detection, ranking.