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Cracking the Data Science Interview

You're reading from  Cracking the Data Science Interview

Product type Book
Published in Feb 2024
Publisher Packt
ISBN-13 9781805120506
Pages 404 pages
Edition 1st Edition
Languages
Authors (2):
Leondra R. Gonzalez Leondra R. Gonzalez
Profile icon Leondra R. Gonzalez
Aaren Stubberfield Aaren Stubberfield
Profile icon Aaren Stubberfield
View More author details

Table of Contents (21) Chapters

Preface 1. Part 1: Breaking into the Data Science Field
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

Searching for your first data science job

Embarking on your data science job search requires careful preparation, diligence, patience, and thick skin. Mental readiness is as vital as technical expertise, with the search often becoming a marathon rather than a sprint. Therefore, maintaining composure and perseverance in this demanding field is paramount for success. To achieve this mindset, it is pertinent that you leverage effective job-hunting skills.

An effective job hunt leverages several tools and resources at your disposal. Job board sites are crucial, functioning as bridges between you and potential employers. Learning how to navigate these platforms effectively can convert them from daunting job databases into your personal gold mines. Equally crucial is a professionally curated portfolio that showcases your technical acumen, problem-solving prowess, creativity, and passion for data science. That’s right – landing a data science job will require more than technical...

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