Cracking the Data Science Interview: Unlock insider tips from industry experts to master the data science field

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.

1144919297
Cracking the Data Science Interview: Unlock insider tips from industry experts to master the data science field

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.

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Cracking the Data Science Interview: Unlock insider tips from industry experts to master the data science field

Cracking the Data Science Interview: Unlock insider tips from industry experts to master the data science field

Cracking the Data Science Interview: Unlock insider tips from industry experts to master the data science field

Cracking the Data Science Interview: Unlock insider tips from industry experts to master the data science field

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$23.99 

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Overview

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.


Product Details

ISBN-13: 9781805120193
Publisher: Packt Publishing
Publication date: 02/29/2024
Sold by: Barnes & Noble
Format: eBook
Pages: 404
File size: 6 MB

About the Author

Leondra R. Gonzalez is a data scientist at Microsoft and Chief Data Officer for tech startup CulTRUE, with 10 years of experience in tech, entertainment, and advertising. During her academic career, she has completed educational opportunities with Google, Amazon, NBC, and AT&T.
Aaren Stubberfield is a senior data scientist for Microsoft's digital advertising business and the author of three popular courses on Datacamp. He graduated with an MS in Predictive Analytics and has over 10 years of experience in various data science and analytical roles focused on finding insights for business-related questions.

Table of Contents

Table of Contents
  1. Exploring the Modern Data Science Landscape
  2. Finding a Job in Data Science
  3. Programming with Python
  4. Visualizing Data and Data Storytelling
  5. Querying Databases with SQL
  6. Scripting with Shell and Bash Commands in Linux
  7. Using Git for Version Control
  8. Mining Data with Probability and Statistics
  9. Understanding Feature Engineering and Preparing Data for Modeling
  10. Mastering Machine Learning Concepts
  11. Building Networks with Deep Learning
  12. Implementing Machine Learning Solutions with MLOps
  13. Mastering the Interview Rounds
  14. Negotiating Compensation
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