If you’re totally new to artificial intelligence (A.I.) and machine learning, you might be wondering which technology jobs demand these skills. Some roles (particularly data scientist) are increasingly reliant on machine learning, meaning you’ll have to know at least some of the underlying concepts in order to access the full range of opportunities out there.

In simplest terms, machine learning centers on algorithms that use data input to “learn” (i.e., improve their efficiency and output). Working within this discipline usually involves building a model based on a “training” dataset and a desired output; the program then does its best to reach that output, tweaking its algorithms in response to feedback as it does so. 

There are several different types of machine learning, including supervised learning, unsupervised learning, and reinforcement learning. Today, technologists utilize it in a number of applications, including (but definitely not limited to) autonomous driving (to help a self-driving car identify obstacles, for example) and content filtering (with time, an algorithm can get very good at flagging questionable text).

According to Burning Glass, which collects and analyzes millions of job postings from across the country, machine learning jobs will grow an astounding 39.3 percent over the next decade. For positions that heavily leverage the technology, the median salary currently stands at $107,000. Perhaps best of all, you don’t necessarily need advanced degrees to land a machine learning job, with the vast majority of postings asking for a bachelor’s degree.

Here’s the full breakdown from Burning Glass of the top technologist jobs requesting machine-learning skills:

As you can see, if you’re interested in a role as a data scientist or data engineer, chances are pretty good that your desired jobs will request these skills. For software developers and engineers, the percentage of jobs requesting these skills will rise significantly over the next decade, as well. 

Machine learning could greatly impact other jobs, as well. It’s pretty clear at this juncture, for example, that managers and executives will also need to become familiar with these concepts and skills. “A.I. is not going to replace managers but managers that use A.I. will replace those that do not,” Rob Thomas, senior vice president of IBM’s cloud and data platform, recently told CNBC.

If you’re totally new to machine learning (and A.I. in general), Hacker Noon offers a useful breakdown of A.I. from a programmer’s perspective. KDNuggets also has a rundown of the basic terms and the technologies involved. In a similar vein is Microsoft’s AI School, which offers lessons in everything from text analytics and object recognition to custom neural-network models. 

Once you’ve figured out some basic concepts, you can head over to OpenAI’s “Gym,” a toolkit for developing and comparing reinforcement algorithms, as well as a set of models and tools for training A.I. and ML. The OpenAI content includes a handy, very extensive tutorial in deep reinforcement learning, which is a key element in many machine-learning jobs.

Last but certainly not least, if you have a computer-science background and you’re familiar with data structures and algorithms, check out Bloomberg’s Foundations of Machine Learning, a free online course.