Book Image

Cracking the Data Science Interview

By : Leondra R. Gonzalez, Aaren Stubberfield
Book Image

Cracking the Data Science Interview

By: Leondra R. Gonzalez, Aaren Stubberfield

Overview of this book

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.
Table of Contents (21 chapters)
Free Chapter
1
Part 1: Breaking into the Data Science Field
4
Part 2: Manipulating and Managing Data
10
Part 3: Exploring Artificial Intelligence
16
Part 4: Getting the Job

Using Python control statements, loops, and list comprehensions

Control statements are used for various tasks. For example, they’re used to filter data based on certain conditions, perform a calculation on each item in a list, iterate through rows in a dataframe, and more. Additionally, list comprehensions are widely used in data science as they provide efficiency and legibility. It’s often used in data cleaning and preprocessing tasks, feature engineering, and more.

Control statements in Python allow you to control the flow of your program’s execution based on certain conditions or loops. The main types of control statements are conditional statements (such as if, elif, and else) and loop statements (such as for and while).

Meanwhile, list comprehensions are a sort of short-hand approach to writing loop statements. More specifically, they are a shorter, more concise syntax for creating a list based on the values of an existing list.

Conditional statements...