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Cracking the Data Science Interview
Cracking the Data Science Interview

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

By Leondra R. Gonzalez , Aaren Stubberfield
$39.99 $27.98
Book Feb 2024 404 pages 1st Edition
eBook
$39.99 $27.98
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eBook
$39.99 $27.98
Print
$49.99
Subscription
$15.99 Monthly

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Product Details


Publication date : Feb 29, 2024
Length 404 pages
Edition : 1st Edition
Language : English
ISBN-13 : 9781805120506
Vendor :
Microsoft
Category :
Concepts :
Table of content icon View table of contents Preview book icon Preview Book

Cracking the Data Science Interview

Part 1: Breaking into the Data Science Field

In the first part of this book, you will learn about the data science profession as it exists in the modern day, and how this relates to your endeavors in the field. This will serve as an introduction to various career paths and help to set expectations in terms of the skills and competencies required to be successful.

This part includes the following chapters:

  • Chapter 1, Exploring Today’s Modern Data Science Landscape
  • Chapter 2, Finding a Job in Data Science
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Key benefits

  • Acquire highly sought-after skills of the trade, including Python, SQL, statistics, and machine learning
  • Gain the confidence to explain complex statistical, machine learning, and deep learning theory
  • Extend your expertise beyond model development with version control, shell scripting, and model deployment fundamentals
  • Purchase of the print or Kindle book includes a free PDF eBook

Description

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.

What you will learn

Explore data science trends, job demands, and potential career paths Secure interviews with industry-standard resume and portfolio tips Practice data manipulation with Python and SQL Learn about supervised and unsupervised machine learning models Master deep learning components such as backpropagation and activation functions Enhance your productivity by implementing code versioning through Git Streamline workflows using shell scripting for increased efficiency

What do you get with eBook?

Product feature icon Instant access to your Digital eBook purchase
Product feature icon Download this book in EPUB and PDF formats
Product feature icon Access this title in our online reader with advanced features
Product feature icon DRM FREE - Read whenever, wherever and however you want
Buy Now

Product Details


Publication date : Feb 29, 2024
Length 404 pages
Edition : 1st Edition
Language : English
ISBN-13 : 9781805120506
Vendor :
Microsoft
Category :
Concepts :

Table of Contents

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

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