Best 13 Masters in Machine Learning in 2024

Columbia University grants a Master’s in Computer Science with a Machine Learning track which is intended for students who wish to develop their knowledge of machine learning techniques and applications. Many topics may be touched upon, depending on the classes students choose from, including causal inference, probabilistic modeling. Thee is a machine learning community at CU that spans multiple departments, schools, and institutes. This group participates in activities like seminars on statistical machine learning, student-led reading groups and social hours, and participation in local events such as the New York Academy of Sciences Machine Learning Symposium.

Cornell University graduate school’s computer science degree (M.S.) is a 4-semester program. Though it’s technically not a degree in machine learning, students can concentrate their courses in artificial intelligence which includes over ten different machine learning classes that students can choose from. These classes cover topics like dimensionality-reduction, clustering, kernels, deep networks, model debugging, tensor languages, dataset bias, language grounding, the ethics of machine learning, and so much more. This program requires research and a thesis, as well as two non-CS graduate courses to make up a “minor.” In addition, students will be required to TA for undergraduate-level CS classes in exchange for their paid tuition and a stipend for living expenses.

In 2019, MIT formed a new college, the Schwarzman College of Computing, to better tackle the gap being found between ever-changing technology and educational systems. MIT hopes to produce “creative computational thinkers and doers with the cultural, ethical, and historical consciousness to use technology for the common good — leaders who will offer the world new technological possibilities grounded in human values.” Their master’s degree in computational science and engineering takes 12-24 months to complete and is heavily research-based. Of the six courses required for graduation, three are chosen by the student as electives. Two of those electives must be chosen from an approved list, which, yes, includes several courses in machine learning.

Carnegie Mellon University’s Master’s of Science in Machine Learning requires future students to have a strong computer science background. They must also understand the complex theory involved, be skilled in programming, and have a knack for mathematics. Under this master’s program, students will concentrate on machine learning, artificial intelligence, NLP, computer vision, etc. It takes between one and three years to finish the degree program.

Georgia Institute of Technology offers a Master’s of Science in Computer Science with a Machine Learning specialization. Future engineers will examine core courses, such as advanced learning, statistics, research, statistical machine learning, and more. They can complete the master’s program in under two years, focusing on deep learning, data mining, artificial intelligence, etc.

The University of Illinois at Urbana-Champaign offers two master’s degrees in computer science: a Master of Computer Science in Computer Science or a Master of Science in Computer Science. The main difference is that the MS in Computer Science is a little more research-based and includes a thesis. The MCS in Computer Science has students increase the breadth of their knowledge by taking additional classes in place of a thesis. Whichever you decide to pursue, both have the option to pursue an artificial intelligence emphasis, which includes several classes about machine learning.

If you’re looking for a degree in machine learning from Stanford, the closest you’ll find is the 45-unit Master of Science in Computer Science program that offers a couple of classes in machine learning. That being said, Standford also offers a certificate of achievement in machine learning for professionals who take the online Machine Learning and/or Machine Learning Strategy and Intro to Reinforcement Learning courses. If students want to take it one step further, they can take a third class to earn a professional certificate in artificial intelligence.

The Master of Science in Artificial Intelligence and Machine Learning at Drexel University is an online program grounded in cutting-edge technology. Students must have a strong background in computer science to apply, whether that’s by completing a bachelor’s or master’s degree in computer science or by completing Drexel’s graduate certificate in computer science. The AI and Machine Learning program can be completed in as little as two years if studying full-time. Graduates will know how to understand the implementation and use of existing artificial intelligence and/or machine learning tools and systems; design, implement, and evaluate a computer-based artificial intelligence and machine learning system, process, component, or program to meet a specific need; understand and communicate the legal and ethical aspects of using artificial intelligence and machine learning in societal contexts; and much more.

Wentworth Institute of Technology’s School of Computing and Data Science offers an M.S. in Applied Computer Science, a full-time degree delivered in a hybrid format. The master’s degree plan, with a concentration in Artificial Intelligence and Machine Learning, gives graduates practical skills to advance their careers in the field. As an online master’s program, students can complete it in under two years. Focus areas include programming, computer systems fundamentals, including computer organizations, operation systems, databases, data communication, and more.

The Department of Computer Science at the University of Arizona offers two kinds of master’s degrees in computer science. The non-thesis option is good, though for someone pursuing machine learning, there are only a few classes (9 out of 30 total credits) available to take that are directly focused on AI or machine learning. If you are interested in research or want to continue on to a Ph.D., then the thesis option will not only let you take the already mentioned classes, but you’ll also be able to use 6 credits toward your thesis, which can be machine-learning- or AI-inspired. This would let you focus half of your degree, 15 out of 30 required credits, on AI and machine learning principles or research. This is the closest you can get to a master’s in machine learning from the University of Arizona.

The Master’s in Computer Science at the Florida Institute of Technology provides future students with relevant technical skills to enter top jobs, including information technology, database information, etc. Its graduates will gain other essentials in developing and designing algorithms, test software, and information systems. FIT’s professors mentor and work closely with students on coursework and research. As an interdisciplinary degree plan, it offers research areas like machine learning, speech recognition, cryptography, computer vision, computer networks, intelligent systems, and others for those who choose the thesis option. The school offers four separate AI and machine learning-focused courses that make up 12 of the 30 required credits.

The Master of Science in Computer Science at the University of North Carolina-Charlotte equips students with planning, design, implementation, testing, computer management systems, applications, and infrastructural skills. Research areas involve 3D HCI, algorithms, artificial intelligence, data mining, machine learning (cloud computing, robotics, wireless networks), and more. Once accepted to the master’s program students can choose the AI, Robotics, and Gaming concentration and take their 9 required credits in AI and machine learning classes. For the capstone class, students can choose to pursue the individual study in AI option.

The School of Medicine at Oregon Health and Sciences University grants a Master’s in Computer Science and Electrical Engineering, a one-and-a-half-year program. Students with undergraduate and graduate-level courses, including computer science, programming, data structures, math calculus, probability, and, statistics can apply for admission into the program. Classes consist of machine learning, natural language processing, speech and signal processing, etc. Students will work with their advisory committee to hand-pick their classes so they can pursue their interests. There are machine learning courses available in both the CS and EE course options as well as machine learning research possibilities for those who are interested in research or continuing on to get a Ph.D. Students can choose to use independent study classes and research credits toward their elective requirements to better focus their time on their AI and machine learning interests.