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Cracking the Data Science Interview

You're reading from   Cracking the Data Science Interview Unlock insider tips from industry experts to master the data science field

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Product type Paperback
Published in Feb 2024
Publisher Packt
ISBN-13 9781805120506
Length 404 pages
Edition 1st Edition
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Authors (2):
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Leondra R. Gonzalez Leondra R. Gonzalez
Author Profile Icon Leondra R. Gonzalez
Leondra R. Gonzalez
Aaren Stubberfield Aaren Stubberfield
Author Profile Icon Aaren Stubberfield
Aaren Stubberfield
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Table of Contents (21) Chapters Close

Preface 1. Part 1: Breaking into the Data Science Field FREE CHAPTER
2. Chapter 1: Exploring Today’s Modern Data Science Landscape 3. Chapter 2: Finding a Job in Data Science 4. Part 2: Manipulating and Managing Data
5. Chapter 3: Programming with Python 6. Chapter 4: Visualizing Data and Data Storytelling 7. Chapter 5: Querying Databases with SQL 8. Chapter 6: Scripting with Shell and Bash Commands in Linux 9. Chapter 7: Using Git for Version Control 10. Part 3: Exploring Artificial Intelligence
11. Chapter 8: Mining Data with Probability and Statistics 12. Chapter 9: Understanding Feature Engineering and Preparing Data for Modeling 13. Chapter 10: Mastering Machine Learning Concepts 14. Chapter 11: Building Networks with Deep Learning 15. Chapter 12: Implementing Machine Learning Solutions with MLOps 16. Part 4: Getting the Job
17. Chapter 13: Mastering the Interview Rounds 18. Chapter 14: Negotiating Compensation 19. Index 20. Other Books You May Enjoy

Exploring Today’s Modern Data Science Landscape

If you’ve picked up this book, chances are that you’ve already heard of data science. It’s arguably one of the fastest-growing, most discussed professions within the tech and STEM space, all while maintaining its relative edge and mystique. That is, many people have heard of data scientists, but very few know what they do, how a data scientist produces value, or how to break into the field from scratch.

In this chapter, we will verify the definition of data science with a practical description. Then, we will discuss what most data science jobs entail, while spending some time describing the distinction between different flavors of data science. We’ll then dive into the various paths into data science and what makes it so challenging to land your first job. We’ll finish the chapter with an overview of the non-negotiable competencies expected of data scientists.

By the end of this chapter...

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