Artificial intelligence, as we know it, has been around since the 1950s, but it’s only within the past decade that it has transitioned from science fiction to everyday reality. Companies we interact with each day— Amazon, Facebook, Google—have fully embraced AI, developing shockingly on-target recommendations engines and increasingly elegant language translation programs.

As more companies adopt AI technologies, demand for qualified machine learning engineers (and other AI-focused roles) is increasing. In fact, we’re in the midst of an AI talent shortage that experts predict won’t be alleviated for many years.

If you want to transition into a cutting-edge role, there has never been a better time to learn how to become a machine learning engineer. And this guide will help you do that.

Through 35 pages of original research and interviews with working machine learning engineers and data scientists, we’ll walk you step by step through everything you need to know to build a career in AI and machine learning.

• You’ll start off by exploring the difference between artificial intelligence, machine learning, and deep learning.

• Then you’ll learn about what it takes to become a machine learning engineer: from education and professional background to hard skills and tools.

• You’ll read exclusive interviews with professionals at top tech companies.

• Finally, you’ll get access to a bonus list of resources for self-study.

Anyone who wants to understand more about the field that is responsible for tech’s most cutting-edge innovations. Whether you’re just curious about artificial intelligence and machine learning or you’ve decided that it is the perfect career path for you, this free ebook is a must-read!