Data Science interviews cover probability, statistics, machine learning, sql & database design, python coding questions, and product sense. Thats why ace the data science interview has a chapter dedicated to every topic - it's everything your looking for for data science, data analyst, and machine learning interviews.
Ace the Data Science Interview PDF has 201 questions from actual data scientist interviews, with full solutions to each problem. These interview problems come from companies like Facebook, Google, Amazon, Microsoft, Netflix, Stripe, Uber and Citadel.
As the volume, speed, and variety of data grows every day, the demand for skilled data scientists and analysts rises. Based on the experience in job interviews or networking with colleagues, we believe that many prospective candidates struggle to pass the initial interview stage because they are unaware of the sample questions they must prepare beforehand. Therefore, in this tutorial, we'll focus on presenting and discussing the most relevant theoretical and practice questions that a candidate might face during an interview.
Ace the Data Science Interview PDF review
Let me start by saying simply that Nick and Kevin (the authors) have produced a wonderful book (a must read). First and foremost, it is a great resource for anyone who wants to learn about data science. It teaches you how to get yourself in the right place at the right time. You'll find yourself asking questions such as "how did he/she get hired?" and "what should I say to get the next position?". Without a plan to do so, your resume is floating around in a sea of other resumes from other hopefulls. This book shows you precisely how to succeed on the most important part of the process - the interview. If the book only ended there, it would still be worth the purchase, however, it doesn't. The author takes the time to walk you through a solid core of skills needed to be successful in the field. He also provides you with the tools to be able to demonstrate these skills during interviews. Finally, he gives you plenty of exercises to reinforce what you have learned. This book is a must read for any aspiring data scientist.