krishnaik06/interview-prepartion-data-science

This repository is a collection of learning materials designed to help people prepare for data science interviews. Created by Krishna Naik, a well-known data science educator, it gathers practice questions, worked examples, and reference notebooks covering the core topics that tend to come up in technical interviews for data science and machine learning roles. The entire repository is built around Jupyter Notebooks, which are interactive documents that combine explanatory text with runnable code. Instead of just reading about a concept, you can see the code behind it and experiment with it yourself. The notebooks walk through common interview topics, showing both the underlying reasoning and the practical implementation of various techniques. Someone preparing for a data science job interview would find this useful. For example, if you are a recent graduate or a self-taught learner heading into your first technical round, you could use these notebooks to review key concepts, test your understanding, and see how experienced practitioners approach typical interview questions. It functions as a structured study guide rather than a full course, letting you focus on the specific topics you need to brush up on. It is worth noting that the README itself is essentially blank beyond the project title, so it does not provide a detailed guide to how the materials are organized or what specific subjects are covered. You would need to explore the notebook files directly to understand the full scope and structure of the content.