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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
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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

Applying scenario-based storytelling

One of the most important aspects of a data scientist’s role is to translate complex datasets into a narrative that people who aren’t data scientists can understand. The ability to present your findings clearly and compellingly is a crucial skill for a data scientist. This section provides a framework for structuring your data story effectively:

  • Begin with your end: Before crunching numbers, clarify your goal. What is the key message you want to communicate? What action do you want to take? A clear objective will guide your analysis, influence your choice of visualizations, and ensure your story resonates with your audience.
  • Know your audience: Understanding your audience’s needs, interests, and level of knowledge will help you present your data meaningfully. Tailor your story to fit your audience – the detail, complexity, and visualizations you use should vary depending on who you’re speaking to.
  • ...
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