Data & AI interview questions, answered properly.
650+ 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.
PractisePython
Core language, data structures, and idioms for data work.
PractiseCoding Patterns
The reusable algorithm patterns behind coding rounds — two pointers, sliding window, hashing, BFS/DFS, DP.
PractiseStatistics & Probability
Inference, distributions, hypothesis testing, A/B tests.
PractiseMachine Learning
Models, evaluation, regularization, the bias–variance tradeoff.
PractiseDeep Learning
Neural nets, backprop, optimization, transformers.
PractisePandas & Data Wrangling
Cleaning, reshaping, GroupBy, joins, performance.
PractiseNLP & LLMs
Embeddings, attention, RAG, prompting, evaluation.
PractiseMLOps
Serving, monitoring, drift, CI/CD, reproducibility.
PractiseData Engineering
Pipelines, Spark, warehousing, data modeling.
PractiseTime Series
Stationarity, ARIMA, forecasting, leakage-free validation.
PractiseData Visualization
Chart choice, dashboards, storytelling with data.
PractiseCase & Behavioral
Product sense, metrics, guesstimates, behavioral rounds.
Practise