To truly thrive in a career in computer programming these days, you need to know more than just basic coding. The future in computing is artificial intelligence (AI) and its very important tool, machine learning (ML).

Mastering machine learning can be very challenging, but it is worth it. Machine learning engineers can earn an average salary of $105,395, according to Glassdoor, which is why machine learning mastery is worthwhile.

What is Machine Learning?

Machine learning is the latest buzzword in the artificial intelligence industry. The term machine learning often gets used interchangeably with artificial intelligence, but the two terms refer to different things.

Artificial intelligence is a broad term that refers to the ability of a machine to do something “smart.” Machine learning is an aspect of artificial intelligence. It is one of the ways a machine can become “smart.”

When artificial intelligence first started, programmers would basically tell the computer what to do, and give it all the data it needed to do the job.

Machine learning doesn’t require all that upfront data dumping. With ML, the computer or machine learns for itself.

This doesn’t just happen magically. Computer programmers need to give the machine parameters or algorithms to help the machine learn properly.

The algorithms that support the machine learning process might be different, depending on the application. For example, an AI that predicts the value of stocks and bonds would have algorithms that might involve tracking certain financial indicators.

An AI that might be used for an ecommerce shopping site would base its machine learning on the behavior of the online shopping customers.

Machine learning is absolutely the future of artificial intelligence, and programmers who want to be in this exciting, lucrative field need to understand machine learning to be a part of it.

Skills Required for Machine Learning Mastery

Machine learning programming is not for everyone. You would not want to become a machine learning engineer if you hated math, for example. Furthermore, ML requires a lot of broad knowledge from a variety of math and technical-related fields.

If you want to become good at machine learning, you should be committed to studying and continual learning to keep up with the latest developments.

Here are some other skills you should have to become good at machine learning:

1. Expertise in Computer Programming

As a foundation to becoming a machine learning engineer, you will need to know how to write computer programs. Certain languages are better for ML than others, and you will probably want to learn a few of them, as each has strengths and weaknesses.

The Python programming language, for example, has specific libraries available for machine learning. For statistics and plots, the R programming language is recommended.

2. Math, Math, and More Math

Machine learning engineers need to have a good grasp of math, and not just plain old addition and subtraction, but advanced math. To become a master machine learning programmer, be ready to learn Linear Algebra and Calculus. You also need to understand Applied Math and Algorithms.

3. Probability and Statistics

Once you master math, you will need to understand probability and statistics. While they are related, probability can be more theoretical in nature, whereas statistics generally deals more with real-world problems. You need both, however, because with artificial intelligence, the computer needs statistics and data to learn, and it will often use probability to make decisions.

The Khan Academy online school has free classes in statistics and probability, which can be a good place to start to see if you are interested in learning more.

Educational Options in Machine Learning

Having a college degree is important for most jobs these days, but with machine learning, other than a Bachelor’s degree, no one-size-fits-all educational path exists as of yet. Some programmers opt for a Master of Science in Computer Science, while others might pursue advanced degree programs in Statistics.

For those who are working and want to expand their skills in their off-hours, online learning opportunities in ML are available. Coursera offers a suite of courses for budding machine learning engineers. The online learning website has also partnered with Johns Hopkins University to provide a specialization in Data Science.

Independent teachers also offer machine learning courses online. Dr. Jason Brownlee, a machine learning expert in Australia, has a website called “Machine Learning Mastery” where he promises to teach ML in a faster, easier way than academic courses.

“The academic approach used to teach machine learning makes me angry. It’s so slow!” he writes on his website.

Machine Learning: The Future of Programming Jobs

No matter what the path towards becoming a machine learning expert, with hard work, study, and discipline, you can join one of the hottest careers of the future. But without standard educational paths for the career as of yet, you will have to chart your own course to succeed in the lucrative field of artificial intelligence.

Andrew Ng, Co-founder of Coursera, writes on Quora: “Every Saturday, you will have a choice between staying at home and reading research papers/implementing algorithms, vs. watching TV….here’s the secret: If you do this not just for one weekend, but instead study consistently for a year, then you will become very good.”

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