Data-Science-Interview-Questions-Answers

Data-Science-Interview-Questions-Answers is a curated collection of interview questions and answers for people preparing for data science roles. The content started as a daily LinkedIn series that the author began in May 2022, posting a new question each day and then summarizing community responses the following day. Those questions and answers are compiled here so readers can review them without following the LinkedIn feed.

The questions are organized into separate Markdown files by topic. Categories covered include machine learning, deep learning, large language models, computer vision (split across three separate parts), statistics, probability, Python programming, SQL and databases, and resume-based questions. Each category links either to a Markdown file in the repository or to a Medium article that covers the same content in a slightly different format.

The questions span both conceptual and practical territory. Conceptual questions ask how specific algorithms work, what the difference between related techniques is, or when to choose one approach over another. Practical questions cover Python coding patterns, SQL query design, and database concepts. Resume-based questions address how to present your work experience and projects in a data science context.

Questions were contributed both by the author and by members of the author's LinkedIn network. The project accepts pull requests so the community can add new questions over time. The README also provides the author's contact details for anyone who wants to submit questions directly.

There is no executable code in this repository. The content consists entirely of Markdown files intended to be read on GitHub or downloaded for study before an interview.