Book Image

Cracking the Data Science Interview

By : Leondra R. Gonzalez, Aaren Stubberfield
Book Image

Cracking the Data Science Interview

By: Leondra R. Gonzalez, Aaren Stubberfield

Overview of this book

The data science job market is saturated with professionals of all backgrounds, including academics, researchers, bootcampers, and Massive Open Online Course (MOOC) graduates. This poses a challenge for companies seeking the best person to fill their roles. At the heart of this selection process is the data science interview, a crucial juncture that determines the best fit for both the candidate and the company. Cracking the Data Science Interview provides expert guidance on approaching the interview process with full preparation and confidence. Starting with an introduction to the modern data science landscape, you’ll find tips on job hunting, resume writing, and creating a top-notch portfolio. You’ll then advance to topics such as Python, SQL databases, Git, and productivity with shell scripting and Bash. Building on this foundation, you'll delve into the fundamentals of statistics, laying the groundwork for pre-modeling concepts, machine learning, deep learning, and generative AI. The book concludes by offering insights into how best to prepare for the intensive data science interview. By the end of this interview guide, you’ll have gained the confidence, business acumen, and technical skills required to distinguish yourself within this competitive landscape and land your next data science job.
Table of Contents (21 chapters)
Free Chapter
Part 1: Breaking into the Data Science Field
Part 2: Manipulating and Managing Data
Part 3: Exploring Artificial Intelligence
Part 4: Getting the Job

Part 1: Breaking into the Data Science Field

In the first part of this book, you will learn about the data science profession as it exists in the modern day, and how this relates to your endeavors in the field. This will serve as an introduction to various career paths and help to set expectations in terms of the skills and competencies required to be successful.

This part includes the following chapters:

  • Chapter 1, Exploring Today’s Modern Data Science Landscape
  • Chapter 2, Finding a Job in Data Science