Data science and AI are among the best (and highest paying) careers in the world right now, so it makes sense to keep increasing your knowledge, and learning from the best. But doing that in an age of information overload isn’t easy.

One way to stay ahead of the game is to ensure you’re reading the best material, and being inspired by the greats while you work from home (or wherever is safe and possible right now), and that means picking the best books and podcasts.

But with a dizzying amount of choice on these two important subjects, it can be hard to know what to read or listen to.

So we’ve done the hard work for you, and chosen the best recent books, and the top podcasts, on both data science and AI, so that you can save time and become better, faster.

Whether you want to brush up on data structures and algorithms, understand the intricacies of machine learning, gain direction and discover good processes, hear from giants in the industry, or be inspired with new ideas, the books and podcasts featured here will accelerate your learning.

Books on data science and AI

The Essential AI Handbook for Leaders presented by Peltarion, with a foreword by Marcus Wallenberg

The book is organized into three sections. The first reveals the possibilities of AI and how we can use it for business and society. The second explains the fundamentals of AI and how it works. The third presents how we can operationalize AI in the business world.

You can read a full review of this title here at Dataconomy, and Peltarion has been gracious enough to offer a free e-book download for all our readers and Data Natives community members.

A Common-Sense Guide to Data Structures and Algorithms: Level Up Your Core Programming Skills 1st Edition by Jay Wengrow

This excellent book is for those that find it difficult to grasp what is going on thanks to other texts being heavy on math jargon and obtuse concepts. It sets out to demystify computer science fundamentals, and does a fantastic job of doing so.

Machine Learning: 2 Books in 1: An Introduction Math Guide for Beginners to Understand Data Science Through the Business Applications by Samuel Hack

Broken into two distinct books, this resource breaks everything down into simple, easy-to-follow explanations of the foundations behind machine learning, from mathematical and statistical concepts to the programming behind them.

Introduction to Computation and Programming Using Python, third edition: With Application to Computational Modeling and Understanding Data by John V. Guttag

This book will take you from little or no Python experience to being able to use it and various Python libraries, including numpy, matplotlib, random, pandas, and sklearn, for problem solving. It covers computational techniques, and some data science tools and techniques, as well as machine learning.

The Atlas for the Aspiring Network Scientist Paperback by Michele Coscia

Billed as an “atlas” rather than focusing on helping you understand just one aspect of computer intelligence and data science, this books aims to help you chart your path to encompass all of the aspects of our field, and ultimately become something different; a pure network scientist.

AI and data science podcasts

Lex Fridman Podcast

While not solely about pure data science and AI, this podcast – which is billed as “conversations about the nature of intelligence, consciousness, love, and power” – is a real treasure trove of amazing discussions and interviews that will keep you inspired and engaged.

Talking Machines

While the team behind this podcast is taking a break to reflect on important issues such as Black Lives Matter, hosts Katherine Gorman and Neil Lawrence have built up an impressive library of episodes that include discussions with experts in the field, industry news, and useful answers to your machine learning questions.

Concerning AI

Ted Sarvata and Brandon Sanders are (at the time of writing) 70 episodes into their deep dive on how AI is affecting our daily lives, and whether it presents a risk to humanity, as many have suggested in recent history.

Data Skeptic

Centered on data science, machine learning, and artificial intelligence, Data Skeptic digs into each topic in detail. For example, a recent episode is a conversation with Yuqi Ouyang, who in his second year of PhD study at the University of Warwick in England, gives details on his work “Video Anomaly Detection by Estimating Likelihood of Representations.”

So there you have it. Four books and four podcasts to help you get ahead in data science and AI. Enjoy, and grow.

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