Cracking the Data Science Interview is an open educational repository that collects study materials, resources, and reference links for preparing for data science interviews. The project organizes content across many fundamental areas of data science, including statistics, probability, SQL, machine learning, and deep learning. It includes cheat sheets that summarize important technical concepts commonly discussed during technical interviews. The repository also provides links to recommended books, tutorials, practice platforms, and blog posts that help learners strengthen their theoretical and practical skills. In addition to conceptual study materials, the project includes interview question banks and case study prompts that simulate real hiring scenarios. The resource is particularly useful for candidates preparing for technical interviews in data science, machine learning, or analytics roles.
Features
- Cheat sheets summarizing key data science concepts
- Interview question banks for machine learning and analytics roles
- Curated links to books, tutorials, and learning resources
- Coverage of SQL, statistics, and probability fundamentals
- Case studies related to real machine learning problems
- Portfolio examples and learning project references