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You're reading from  Cracking the Data Science Interview

Product typeBook
Published inFeb 2024
PublisherPackt
ISBN-139781805120506
Edition1st Edition
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Authors (2):
Leondra R. Gonzalez
Leondra R. Gonzalez
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Leondra R. Gonzalez

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.
Read more about Leondra R. Gonzalez

Aaren Stubberfield
Aaren Stubberfield
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Aaren Stubberfield

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.
Read more about Aaren Stubberfield

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What this book covers

In Chapter 1, Exploring the Modern Data Science Landscape, we begin our journey with a brief but valuable overview of the contemporary landscape of data science and AI.

In Chapter 2, Finding a Job in Data Science, we will introduce data science roles and their various categories.

In Chapter 3, Programming with Python, you will familiarize yourself with the most common and useful tasks and operations in the Python language.

In Chapter 4, Visualizing Data and Storytelling, you will learn techniques for telling engaging data stories.

In Chapter 5, Querying Databases with SQL, you will dive into the world of databases, understanding their design and how to query them to acquire data.

In Chapter 6, Scripting with Bash and Shell Commands in Linux, you will boost your operating system skills with the power of bash and shell commands, enabling you to interface with multiple technologies either locally or in the cloud.

In Chapter 7, Using Git for Version Control, we explore the most useful commands in Git for project collaboration and reproducibility.

In Chapter 8, Mining Data with Probability and Statistics, you will understand some of the most relevant topics in probability and statistics that serve as the foundation for many ML models and assumptions.

In Chapter 9, Understanding Feature Engineering and Preparing Data for Modeling, you will use your understanding of descriptive statistics to create clean, “machine-legible” datasets.

In Chapter 10, Mastering Machine Learning Concepts, you will learn about the most used ML algorithms, their assumptions, how they work, and how to best evaluate their performance.

In Chapter 11, Building Networks with Deep Learning, we take a step further into building and evaluating neural networks in various applications while also touching base on the latest advancements in AI.

In Chapter 12, Implementing Machine Learning Solutions with MLOps, we will review the data science process, tools, and strategies to effectively design and implement an end-to-end ML solution.

In Chapter 13, Mastering the Interview Rounds, you will learn the best techniques to successfully bypass technical and non-technical factors at every stage of the interview process.

In Chapter 14, Negotiating Compensation, you will learn to optimize your earning potential.

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Cracking the Data Science Interview
Published in: Feb 2024Publisher: PacktISBN-13: 9781805120506

Authors (2)

author image
Leondra R. Gonzalez

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.
Read more about Leondra R. Gonzalez

author image
Aaren Stubberfield

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.
Read more about Aaren Stubberfield