Develop your skills and prepare for your interview using over 500+ real questions from the biggest data companies in data science.
In an A/B test, how can you check if assignment to the various buckets was truly random?
Test your generalized data science knowledge against your peers.
Should take around 15 to 30 minutes to complete.
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Understanding how to solve problems before pulling data and how to showcase analytical knowledge to empower business decisions.
These questions test how to write complex implementations of data structures and algorithms for machine learning and engineering focused roles.
SQL & Analysis
Tests data analytics, ability to pull your own data for building models, and different interpretation of datasets and metrics.
Test basic skills within coding in Python such as text parsing, reading files for writing scripts or building features out of datasets in Pandas.
Statistics & A/B Testing
Needed to understand the basics of statistics, experiment design, and how to effectively measure and implement A/B tests.
Machine Learning & System Design
Understanding of how to build, deploy, and test machine learning models in production as well as how to architecting database design for scale.
A focus on testing the interpretation and validation of model building, model case studies, and showcasing an understanding of tradeoffs between technical and business decisions.
Based on understanding the principles behind many algorithms and models.
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Access 500+ interview questions with solutions we have in our database, including real take-home exercises companies use in interviews.
Work on practice questions directly from our in-browser code editor.
Get customized practice recommendations and study guides for your goals based on responses to our challenge questions
Full access to over 30 hours of course content that specifically geared towards reviewing what you need to know to ace your technical interviews.