# DataInterview > Ace Data Scientist, Data Engineer, ML/AI Engineer, and Quant interviews. Practice 800+ coding problems, 4,000+ interview questions, and premium courses. ## About DataInterview (https://www.datainterview.com) is an interview preparation platform for Data Scientist, Data Engineer, ML/AI Engineer, and Quant roles. It offers 800+ coding problems, 4,000+ interview questions, learning courses, 1:1 coaching, and a question bank used by candidates targeting companies like Google, Meta, Amazon, Apple, and more. ## Courses DataInterview offers structured learning courses covering key interview topics: - [AB Testing](https://www.datainterview.com/courses/ab-testing): Covers experiment design, hypothesis testing, validity threats, statistical inference, and practice cases. 82 lessons. - [Applied Statistics](https://www.datainterview.com/courses/applied-statistics): Core statistics concepts for data science interviews. - [Causal Inference with Python](https://www.datainterview.com/courses/causal-inference): Beginner-friendly causal inference for product data science and interviews, with Python case studies covering observational adjustment and quasi-experimental methods. Taught by Dan Lee, Data & AI Lead. - [Case in Point](https://www.datainterview.com/courses/case-in-point): Case study interview preparation. - [Cloud Data Warehousing](https://www.datainterview.com/courses/cloud-data-warehousing): Deep-dive into Snowflake, BigQuery, Redshift, and Databricks. Covers warehouse internals, cost optimization, and cloud DW design problems. - [Data Engineering System Design](https://www.datainterview.com/courses/data-engineering-system-design): Design data warehouses, streaming pipelines, and ETL systems. Covers the 14 most-asked DE design problems at Airbnb, Uber, Netflix, and top data-driven companies. - [Data Modeling](https://www.datainterview.com/courses/data-modeling): Master schema design, normalization trade-offs, and real-world data modeling patterns. - [Data Science Coding](https://www.datainterview.com/courses/data-science-coding): Python and pandas coding for data science interviews. - [Estimation for Trading Interviews](https://www.datainterview.com/courses/estimation-trading-interviews): Master Fermi estimation and mental math for Jane Street, Optiver, IMC, and top trading firms. - [Financial Mathematics](https://www.datainterview.com/courses/financial-mathematics): Master stochastic calculus, Black-Scholes, and derivatives pricing for quant interviews. - [Machine Learning](https://www.datainterview.com/courses/machine-learning): ML fundamentals, algorithms, and interview patterns. - [ML System Design](https://www.datainterview.com/courses/machine-learning-system-design): End-to-end ML system design for interviews. - [Mock Interview Recordings](https://www.datainterview.com/courses/mock-interview-recordings): Real mock interview examples with feedback. - [Probability for Quant Interviews](https://www.datainterview.com/courses/probability-quant-interviews): Master the probability puzzles asked at Jane Street, Citadel, Two Sigma, and top quant firms. - [Product Sense](https://www.datainterview.com/courses/product-sense): Product metrics, experimentation, and business case interviews. - [SQL](https://www.datainterview.com/courses/sql): SQL interview preparation with real-world query problems. - [System Design](https://www.datainterview.com/courses/system-design): Go from blank whiteboard to complete architecture in 45 minutes. Covers the 14 most-asked design problems at Google, Meta, Amazon, and top tech companies. - [Trading Systems Design](https://www.datainterview.com/courses/trading-systems-design): Design matching engines, market making systems, and low-latency trading infrastructure for quant interviews. ### Causal Inference with Python The course teaches how to turn product questions into credible causal studies, choose an identification strategy, run the analysis in Python, check assumptions, interpret uncertainty, and make a decision-ready recommendation. - [Why Correlation Isn't Causation](https://www.datainterview.com/courses/causal-inference/why-causality) - [Causal Inference Interview Framework](https://www.datainterview.com/courses/causal-inference/interview-framework) - [Regression Adjustment in Python](https://www.datainterview.com/courses/causal-inference/regression-adjustment) - [Regression Discontinuity in Python](https://www.datainterview.com/courses/causal-inference/regression-discontinuity) - [Difference in Differences in Python](https://www.datainterview.com/courses/causal-inference/difference-in-differences) - [Synthetic Control in Python](https://www.datainterview.com/courses/causal-inference/synthetic-controls-matched-markets) ## Projects Hands-on data science projects inspired by real companies. Build end-to-end ML solutions from business problem to deployment. - [Google Flights Airfare Forecast](https://www.datainterview.com/projects/google-flights-airfare-forecast/business-problem): Build an end-to-end airfare prediction model inspired by Google Flights' price forecasting feature. 9 lessons. - [PayPal Fraud Detection](https://www.datainterview.com/projects/paypal-fraud-detection/business-problem): Design and implement a fraud detection pipeline modeled after PayPal's transaction monitoring system. 9 lessons. - [DoorDash Fraud Detection](https://www.datainterview.com/projects/doordash-fraud-detection/business-problem): Tackle fraud detection for a food delivery platform using real-world DoorDash-inspired scenarios. 8 lessons. - [AWS Realtime News Sentiment](https://www.datainterview.com/projects/aws-realtime-news-sentiment/business-problem): Build a real-time news sentiment analysis pipeline using AWS services and NLP techniques. 10 lessons. - [Facebook Storefront Causal Analysis](https://www.datainterview.com/projects/facebook-storefront/facebook-storefront): Apply causal inference methods to analyze the impact of Facebook's storefront feature on user engagement. 2 lessons. ## Coding Practice - [Coding Challenges](https://www.datainterview.com/coding): 800+ coding problems in Python, SQL, and more. Filterable by company, role, and topic. - [Question Bank](https://www.datainterview.com/questions): 4,000+ behavioral, product sense, ML, system design, and technical interview questions from real interviews. ## Coaching - [1:1 Coaching](https://www.datainterview.com/coaching): Personalized mock interviews and career coaching with instructors from Google, Meta, Amazon, and other top companies. Available for data science, ML engineering, AI engineering, and quant roles. ## Bootcamps - [Data Scientist MasterClass](https://www.datainterview.com/bootcamp/ds): Live class bootcamp for data scientist interview preparation. - [MLE MasterClass](https://www.datainterview.com/bootcamp/mle): Live class bootcamp for machine learning engineer interview preparation. ## Target Roles DataInterview covers preparation for the following roles: - Data Scientist - Machine Learning Engineer - AI Engineer - AI Researcher - Data Analyst - Data Engineer - Quantitative Researcher ## Blog - [Blog](https://www.datainterview.com/blog): Articles on interview tips, career advice, and technical deep dives for data and AI professionals. ## Pricing - [Pricing](https://www.datainterview.com/pricing): Free tier with limited access. Premium subscription for full course access, coding challenges, and question bank. ## Links - Website: https://www.datainterview.com - Courses: https://www.datainterview.com/courses - Projects: https://www.datainterview.com/projects - Coding: https://www.datainterview.com/coding - Coaching: https://www.datainterview.com/coaching - Blog: https://www.datainterview.com/blog - Pricing: https://www.datainterview.com/pricing