Data & AI interview questions, answered properly.
500+ of the questions you'll actually be asked — SQL, Python, statistics, machine learning, deep learning, and LLMs — each with a clear, worked answer, the trap to avoid, and a link to learn it in depth. Filter by the role you're interviewing for.
SQL
Joins, aggregation, window functions, query tuning.
Python
Core language, data structures, and idioms for data work.
Coding Patterns
The reusable algorithm patterns behind coding rounds — two pointers, sliding window, hashing, BFS/DFS, DP.
Statistics & Probability
Inference, distributions, hypothesis testing, A/B tests.
Machine Learning
Models, evaluation, regularization, the bias–variance tradeoff.
Deep Learning
Neural nets, backprop, optimization, transformers.
Pandas & Data Wrangling
Cleaning, reshaping, GroupBy, joins, performance.
NLP & LLMs
Embeddings, attention, RAG, prompting, evaluation.
MLOps
Serving, monitoring, drift, CI/CD, reproducibility.
Data Engineering
Pipelines, Spark, warehousing, data modeling.
Time Series
Stationarity, ARIMA, forecasting, leakage-free validation.
Data Visualization
Chart choice, dashboards, storytelling with data.
Case & Behavioral
Product sense, metrics, guesstimates, behavioral rounds.