Preface

In today’s dynamic technological landscape, the demand for skilled professionals in artificial intelligence (AI) and data science roles has surged, and the data science job market is increasingly saturated by various levels of data science and AI employees. This book is a comprehensive guide, crafted to equip both aspiring and seasoned individuals with the essential tools and knowledge required to navigate the intricacies of data science interviews. Whether you’re stepping into the AI realm for the first time or aiming to elevate your expertise, this book offers a holistic approach to mastering the fundamental and cutting-edge facets of the field.

The chapters within this book span a wide spectrum of critical subjects, from programming with Python and SQL to statistical analysis, pre-modeling and data cleaning concepts, machine learning (ML), deep learning, Large Language Models (LLMs), and generative AI. We aim to provide a comprehensive review and update on the foundational concepts while also delving into the latest advancements. In an era marked by the disruptive potential of language models and generative AI, it’s imperative to continually hone your skills. This book serves as a compass, guiding you through the intricacies of these transformative technologies, ensuring you’re poised to tackle the challenges and harness the opportunities they present.

Moreover, beyond technical prowess, we delve into the art of interviewing for AI roles, offering guidance on how to ace interviews and negotiate compensation effectively. Additionally, crafting a standout résumé tailored for data science roles is a crucial step, and our guide offers insights into writing compelling résumés that capture attention in a competitive job market. As AI reshapes industries and innovation accelerates, now is the ideal time to embark on or advance in your data science journey. We invite you to dive into this comprehensive resource and embark on your path to mastering the dynamic world of data science and AI.

Who this book is for

If you are a seasoned or young professional who needs to brush up on your technical skills, or you are looking to break into the exciting world of the data science industry, then this book is for you.

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.

To get the most out of this book

To get the most out of this book, you should have a basic knowledge of Python, SQL, and statistics. However, you will also benefit from this book if you have familiarity with other analytical languages, such as R. By brushing up on critical data science concepts such as SQL, Git, statistics, and deep learning, you’ll be well-equipped to crack through the interview process.

Software/hardware covered in the book	Operating system requirements
Python 3.12	Windows, macOS, or Linux
Bash	Linux
Jupyter Notebooks	Windows, macOS, or Linux

Conventions used

There are a number of text conventions used throughout this book.

Code in text: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles. Here is an example: The split() method can be used to split s into individual words: words = s.split().

A block of code is set as follows:

x = 5
print(type(x)) # <class 'int'> 

Bold: Indicates a new term, an important word, or words that you see on screen. For instance, words in menus or dialog boxes appear in bold. Here is an example: “The increased computing power and the development of advanced algorithms, especially in machine learning (ML) and deep learning (DL), have made it possible to efficiently process and analyze massive amounts of data.”

Tips or important notes

Appear like this.

Special Note

The prevalence of accessible AI technology has exploded over the past few months, particularly over the course of writing this book. We encourage our readers to utilize AI during their educational journey, leveraging tools such as Chat GPT to test your newly acquired skills. Long gone are the days where you browse StackOverFlow for hours for your specific inquiry. Now, the power of asking for help is right at your fingertips.

Even we, the authors of this book, leveraged generative AI to aid in minor editorial tasks and creating code examples. However, rest assured that humans wrote the content and laid out what is covered in the book! In this new era, we just wanted to make our readers aware of how we used the tool.

Get in touch

Feedback from our readers is always welcome.

General feedback: If you have questions about any aspect of this book, email us at [e-mail] and mention the book title in the subject of your message.

Errata: Although we have taken every care to ensure the accuracy of our content, mistakes do happen. If you have found a mistake in this book, we would be grateful if you would report this to us. Please visit www.packtpub.com/support/errata and fill in the form.

Piracy: If you come across any illegal copies of our works in any form on the internet, we would be grateful if you would provide us with the location address or website name. Please contact us at [e-mail] with a link to the material.

If you are interested in becoming an author: If there is a topic that you have expertise in and you are interested in either writing or contributing to a book, please visit authors.packtpub.com.

Share Your Thoughts

Once you’ve read Cracking the Data Science Interview, we’d love to hear your thoughts! Please click here to go straight to the Amazon review page for this book and share your feedback.

Your review is important to us and the tech community and will help us make sure we’re delivering excellent quality content.

Download a free PDF copy of this book

Thanks for purchasing this book!

Do you like to read on the go but are unable to carry your print books everywhere?

Is your eBook purchase not compatible with the device of your choice?

Don’t worry, now with every Packt book you get a DRM-free PDF version of that book at no cost.

Read anywhere, any place, on any device. Search, copy, and paste code from your favorite technical books directly into your application.

The perks don’t stop there, you can get exclusive access to discounts, newsletters, and great free content in your inbox daily

Follow these simple steps to get the benefits:

1. Scan the QR code or visit the link below

https://packt.link/free-ebook/978-1-80512-050-6

2. Submit your proof of purchase
3. That’s it! We’ll send your free PDF and other benefits to your email directly