Are you currently in the job market for a data-focused role? Or perhaps you are looking to expand your understanding of the machine learning process? If so, then we have just the video for you!

We just published a mock data science job interview on the YouTube channel. This is a full-length interview between Keith Gali and Kylie Ying, two experienced developers in the world of data science.

This video will provide you with an inside look at what a data science interview is like, as well as valuable insights and tips for anyone looking to pursue a career in this field.

The video course is broken down into several sections, starting with an overview of the video format and structure. Next, Keith kicks off the interview with some introductory behavioral questions to help you get to know Kylie better. From there, they dive into a social media platform bot issue task overview, which serves as the main topic of the interview.

Throughout the interview, Kylie shares her expertise on topics such as building a dataset for training/testing purposes, feature vectorization, and model implementation details. One of the highlights of the interview is when she discusses what features to investigate regarding the bot issue and how to approach collecting data to train models to detect bots.

If you are curious about the technical implementation details, Kylie also shares some insights into the python libraries and cloud services that she uses in her work.

The video ends with a post-interview breakdown and analysis, which provides valuable insights into how to improve your performance during a data science interview.

This video is perfect for anyone looking to break into the data science field or expand their knowledge of machine learning. Consider pausing after each question and thinking about how you would answer them, so you can get the most out of this course. Don't miss this opportunity to learn from two experts in the field of data science!

Watch the video on the YouTube channel (1.5 hour watch).