Best Master's Programs in Machine Learning & Artificial Intelligence

Several master's degree programs in machine learning and artificial intelligence prefer or require applicants to have a degree in a science, technology, engineering, or mathematics (STEM) related field. Typically, this degree is a Bachelor of Arts (BA) or Bachelor of Science (BS) in Computer Science, but other areas, such as software engineering and STEM fields may be accepted. These computer- and technology-related fields help equip students with the computer skills needed to succeed in the master's program, as well as providing students with a solid foundation of knowledge in the field.

The admissions standards for machine learning and artificial intelligence master's programs vary between different schools, but all applicants are expected to hold at least a bachelor's degree. Usually, programs have preferences or requirements for the field of study of the bachelor's degree and some programs require a minimum GPA, typically around a 3.0.

Several master's programs in the field also require or prefer applicants to have some prior work experience. Depending on the program, if a student does not have the required work experience, they may be required to complete additional coursework or a certificate program in computer science. Some programs have prerequisite course requirements in areas such as probability, statistics, or discrete mathematics. Other standard application materials for these degree programs include transcripts, GRE scores, letters of recommendation, a resume, and a personal statement/statement of purpose.

Earning a master's degree in machine learning and artificial intelligence can help equip students with the skills needed for a wide range of specialized careers. These programs provide opportunities for students to gain real-world experience through hands-on learning opportunities and projects. Students can also further develop their leadership skills to take on advanced positions within their workplace. Graduates with a master's degree are not only prepared for these advanced positions but can also benefit from the increased pay they typically offer. According to PayScale.com, the median annual salary for those with an MS in Artificial Intelligence was $102,669, as of April 2021.

When choosing a program, students should first make sure that a master's in machine learning and artificial intelligence is the right program for their specific career goals. For instance, students considering a data science master's vs. a machine learning master's need to consider the breadth of each degree. Data science programs are broader, while machine learning is a subfield of data science and is more specific.

Once students are sure that machine learning and artificial intelligence programs align with their interests, they can begin comparing formats and unique characteristics of programs. Students should compare full- and part-time programs, online or evening courses for flexibility, and additional dual degrees, certificates, or hands-on learning options that programs offer. Finally, the cost and location of a program may limit a student's choice of schools.

Coursework for master's degree programs in machine learning and artificial intelligence is unique to each program, but in general, includes many math- and computer science-related courses. Students usually take between 30 and 45 credits of coursework that is divided into core, required courses and some elective courses. It is fairly common for these master's programs to conclude with a culminating experience that pulls students' knowledge and experience together to help prepare them for a career after graduation. Some of these programs can be completed in as little as 15 months, while others take closer to 2 years to complete. Learn more about the curriculum below.

Machine Learning & Artificial Intelligence Foundational Courses

Master's programs that offer elective courses may require between 5 and 7 core courses, while programs that consist solely of core courses could have around 10 core courses. These main courses focus on providing students with the theories and skills required for machine learning, foundational knowledge in artificial intelligence, and complex math skills that are the basis for data analysis in the field. Commonly included in the core courses is a final capstone course. Some programs include a 2-part capstone, while others require a final capstone project that could be an independent research project or practicum experience. Other possible topics for core courses include:

• Programming
• Introduction to artificial intelligence
• Machine learning
• Deep learning
• Data analysis
• Probability and statistics
• Software development

Machine Learning & Artificial Intelligence Specialist & Elective Courses

Depending on the program, students could take between 2 and 7 elective courses to round out their degree. Electives give students the chance to explore different areas of interest within the fields of machine learning and artificial intelligence. Some of these courses could help prepare students for a specific job in the field or equip them with practical skill sets. Usually, students can choose their electives from an approved list, which could be divided into different categories of courses, such as computation and algorithms, data science and analytics, or applications of artificial intelligence and machine learning. Some examples of electives include:

• Algorithms
• Computer vision
• Artificial intelligence programming
• Introduction to robotics
• Data mining
• Theory of computation

Licensure & Certification in Machine Learning & Artificial Intelligence

Licensure and certification are not usually required for machine learning and artificial intelligence professionals. However, professional certifications in the field are available. Some professionals may pursue certification in specific types of software programs that they use regularly or they can pursue professional certification for specific positions. For instance, the Artificial Intelligence Board of America (ARTiBA) offers the Artificial Intelligence Engineer certification and the Global Tech Council offers the Certified Machine Learning Expert certification. These certifications require students to pass an exam after meeting qualifications.

The field of artificial intelligence can also be controversial when it comes to ethics, and therefore, licenses such as the Responsible AI Licenses (RAIL) are also available to promote the responsible use of technology.

While capstone courses are common in MS in Machine Learning and Artificial Intelligence programs, practicum and/or internship opportunities are more common. Generally, these experiences are meant to help prepare students for their future careers through hands-on learning. These experiences generally have students working on specific projects or research opportunities to allow them to apply the knowledge they have obtained throughout the program. Internships may be external or take place on campus in the school's laboratories. Typically, internships and/or practicums happen in the summer when students have more time to dedicate to the experience.

At the doctoral level, students can pursue machine learning Doctor of Philosophy (PhD) programs or artificial intelligence PhD programs. Students may also consider other related degree programs, depending on their interests, such as a machine learning PhD or a statistics PhD.

PhD in Machine Learning jobs include those in research, academia, and the technology industry. These doctoral programs usually require a doctoral thesis and take at least 3 years or more to complete. The curriculum for these programs is highly customizable to give students the chance to focus their studies in areas of interest or those pertaining to their research.

Graduates with their master's degree in machine learning and artificial intelligence are usually prepared to take on advanced, leadership roles within the fields of computer and data science. Graduates can work a wide range of positions, including a machine learning engineer, data scientist, and more. Jobs are also available in an array of settings and industries, such as working for the government, colleges and universities, computer systems design services, software publishers, software developers and more. Some examples of possible career outcomes for graduates with their master's in machine learning and artificial intelligence include:

• Computer and information research scientist
• AI engineer
• AI scientist
• Software engineer
• User experience specialist
• Machine learning researcher
• Data science specialist
• Data analyst

Job Outlook for a Master's in Machine Learning & Artificial Intelligence

In general, the fields of computer science and technology are growing rapidly as the need for technology in most industries grows. The need for experts who understand this technology and can utilize it to analyze data and perform various tasks is also growing. Typically, this growth is at a faster than average rate. For example, according to the U.S. Bureau of Labor Statistics (BLS), the job outlook for computer and information research scientists was 15% from 2019 to 2029, which is much faster than the national average of 4%. The job outlook for software developers was even higher at 22% for the same decade. Overall, the job outlook for graduates in the field is positive, as they will qualify for numerous positions within a growing field.

How to Become a Computer and Information Research Scientist

Computer and information research scientists include careers in areas such as programming and robotics. Typically, these professionals need to have at least a master's degree, but there are some entry-level positions, usually in the government, that may only require a bachelor's degree. Professionals in these positions often hold a degree in computer science, computer engineering, and other closely related fields. Depending on the area in which they work, specialized skills or knowledge could be required, such as some background in biology for those in biomedical applications. These scientists need to have strong analytical, math, and critical-thinking skills.

Computer and information research scientists examine complex issues in computing, find new uses for existing technology, create new computing technology, and make other advances in the field that can in turn advance other fields. This usually requires them to work closely with other scientists and engineers to solve problems by conducting and analyzing experiments. Their findings can be presented in scientific journals and conferences. As of 2020, the BLS reported that the median annual salary for computer and information research scientists was $126,830.

How to Become a Software Developer

Software developers include both systems software developers and applications software developers. To become a software developer, students need to have at least a bachelor's degree, but some employers prefer those with a master's degree. These developers also have to have strong computer programming skills, which requires these professionals to stay updated on the latest computer languages and tools in the field. Software developers may also be required to have specialized knowledge of the field in which they work to better create programs for that specific area. Communication, analytical, and problem-solving skills are essential for these workers.

Software developers work to create computer programs by understanding the need and goal of a program and then designing the specific aspects of the program. This process requires a lot of documentation, collaboration, and testing to ensure that the end program functions as it is supposed to. Software developers can also work with existing programs and provide maintenance and upgrades as needed. Per the BLS, the median annual salary for software developers was $110,140, as of 2020.

Funding is available from diverse sources for students who need help covering the cost of tuition, fees, books, materials, housing, and other costs of earning their master's degree. Each year, students should be sure to fill out their Free Application for Federal Student Aid (FAFSA) to check their eligibility for federal and state loans and grants. Students can then check available financial aid options at their school of interest and outside organizations. Depending on their qualifications, students may be able to find tuition discounts, assistantships, or scholarships that can help them pay for the rest of their education.

Scholarships are commonly available from college and university departments and other outside organizations pertaining to the field. For students earning their master's in machine learning and artificial intelligence, a couple of scholarship examples include:

• Boston University Department of Computer Science Scholarships- Students at Boston University who are pursuing their MS in Artificial Intelligence can compete for these scholarships if they have a 3.0 or higher GPA. The scholarships award between $3,000 a semester and 50% tuition for full-time students or 100% tuition for part-time students and focus on minorities, women, and high-achieving students.
• The Simplr Artificial Intelligence and Technology Scholarship- Simplr is an organization that is involved in machine learning and artificial intelligence and offers a $7,500 scholarship to undergraduate or graduate student winners of their annual essay contest. Students must be studying computer science, information technology, or another related subject and write about a topic concerning artificial intelligence (AI), the Internet of Things (IoT), Blockchain technology and Intellectual Property (IP) law.