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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

Final words

As we draw the curtain on this journey toward cracking the data science interview, let us take a moment to reflect on the vast amount of knowledge and skills you have now acquired. From understanding the dynamic landscape of data science in Chapter 1 to mastering the art of negotiation in Chapter 14, this book has been a comprehensive guide, aiming to sculpt you into a formidable candidate for your next data science role.

You have traversed the intricacies of technical interviews, delved deep into Python programming, SQL, machine learning, version control, and even explored the revolutionary realms of deep learning and MLOps. But beyond the technicalities, you have learned to present yourself, your skills, and your passion for data science in a way that resonates with recruiters and hiring managers. You have been equipped not just with knowledge, but also with the confidence to apply it effectively to real-world scenarios.

As you step into the job market, remember...

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