Machine Learning Graduate Degree Programs

Comparing Graduate Degrees in Machine Learning

Master of Science in Machine Learning

A machine learning master's degree might include courses in psychology (cognitive science), deep learning, natural language processing and programming (particularly with Python). Most applicants have background knowledge or a bachelor's degree in computer science or applied mathematics. Programs last 1-2 years and prepare students for rewarding careers at startups, massive technology companies like Apple and Google, or nonprofit research organizations. To apply, students must send in their transcripts, GRE test scores and letters of recommendation from previous professors.

Master of Science in Data Science

In a data science master's degree, students learn how to gather, analyze and make use of huge swaths of data. After completing core courses, students develop a specialty by choosing from a range of elective classes. By concentrating their electives in machine learning and artificial intelligence, students are prepared with a skill-set that can lead to higher salaries at work. Applicants should have a bachelor's degree in a related subject, extensive background knowledge of discrete mathematics, and a GPA of at least 3.0.

Ph.D. in Machine Learning

Ph.D. programs offer fully-funded research opportunities for students to test the limits of machine learning technology. In a Ph.D. program, a candidate works with experts in the field to develop, carry-out and present original research. Applicants should have at least a bachelor's degree (if not a master's) in a related field and prior experience working in computer science or cognitive science research. Graduates can rise to top positions at corporations that desire machine learning expertise or continue research at a university.

What Can You Do With a Graduate Degree in Machine Learning?

Machine Learning Engineer

The goal of a machine learning engineer is to achieve artificial intelligence in their company's computer systems. That means that computers are able to learn for themselves and complete tasks they were never specifically programmed to do. Engineers build programs and test new technologies. Technology companies like Apple, Google, and Amazon employed machine learning experts to help them run their businesses more efficiently.

Data Scientist

Data scientists must be able to gather, read, analyze and make predictions based off of data sets. They make data usable for their clients. Machine learning allows data scientists to automate the process of analyzing data, thus data scientists with graduate-level experience in machine learning often earn higher salaries. Nearly every growing company uses data to advance their profits, thus data scientists can find work in a variety of industries.

Machine Learning Researcher

While machine learning engineers help to automate computer programs based on previously known techniques, researchers test the limits of the field. They may help design new products or test things like self-driving cars. Machine learning researchers can work in a lab for a government agency, nonprofit laboratory or technology company. They are given the resources to conduct experiments and expand machine learning applications.

Professor of Machine Learning

A Ph.D. in machine learning qualifies graduates to teach at the university level. Professors have access to resources to complete independent research projects. They could research innovations in the science and industry of machine learning or write policy about ethics for this emerging technology. All the while, professors help to educate and train the next generation of machine learning scientists.

Sources: **www.bls.gov, *www.payscale.com

By completing a graduate degree in machine learning students equip themselves with highly-desired skill-set. They can go on to careers in research, product design, or teaching.