If you're completely unfamiliar with AI and machine learning, you might wonder which technology jobs require these skills. Some roles (particularly data scientists) are increasingly dependent on machine learning. This means that you need to know at least some of the underlying concepts to access any opportunity.
Simply put, machine learning is focused on algorithms that use data input to “learn” (i.e. improve efficiency and output). Working within this discipline typically involves building a model based on the “training” dataset and the output of your choice. The program does its best to reach its output and fine-tunes the algorithm according to feedback.
There are several different types of machine learning, such as monitored learning, unsupervised learning, and reinforcement learning. Today, engineers use it in many applications, including (but not limited to) self-driving (which helps self-driving cars identify obstacles) and content filtering (over time, algorithms are very good at flagging suspicious text).
According to Burning Glass, when collecting and analyzing millions of job postings from across the country, machine learning jobs will increase by an astounding 39.3% over the next decade. For positions that make a significant use of technology, the median salary is currently $107,000. Perhaps more than anything, you don't necessarily need an advanced degree to acquire a machine learning job, and most submissions are looking for a bachelor's degree.
This is a complete breakdown from the burning of work for top technologists who demand machine learning skills.
As you can see, if you are interested in the role as a data scientist or data engineer, it is very likely that the desired job will require these skills. For software developers and engineers, the proportion of jobs that require these skills will also rise significantly over the next decade.
Machine learning can have a major impact on other jobs as well. For example, at this point, it is clear that managers and executives should also be familiar with these concepts and skills. “AI is not going to replace managers, but managers who use AI will replace managers who don't,” Rob Thomas, senior vice president of IBM's cloud and data platforms, recently told CNBC.
If you're not accustomed to machine learning (and AI in general), Hacker Noon offers a useful breakdown of AI from a programmer's perspective. Kdnuggets also has a summary of basic terminology and related technologies. Similarly, there is Microsoft's AI School. It offers everything from text analysis and object recognition to custom neural network models.
Once you've found some basic concepts, you'll have access to Openai's “gyms,” a toolkit for developing and comparing enhancement algorithms, as well as a set of models and tools for AI and ML training. OpenAI content includes useful and extremely extensive tutorials in deep reinforcement learning, an important element of many machine learning jobs.
Last but not least, if you have a background in computer science and are familiar with data structures and algorithms, check out Bloomberg's Machine Learning foundation, a free online course.
