Guide to Earning a Master's in Machine Learning
Updated November 9, 2023
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Machine learning (ML), a subset of automated intelligence (AI), uses algorithms and data to help computers learn without direct human interference. According to LinkedIn, ML engineer was one of the fastest-growing job titles from 2017-2022.
Companies continuously invest time and resources into machine learning, which currently accounts for the highest percentage of funding in AI. The machine learning industry covers multiple sectors and has an expected annual growth rate of 39% from 2020-2030, according to Market Research Future.
A master's in machine learning program teaches individuals the fundamental principles and skills to pursue careers in ML. The following page discusses the costs, benefits, and career choices of attending a master's in ML program.
Why Get a Machine Learning Degree?
Walter Pitts and Warren McCulloch published the first paper regarding machine learning in 1943. This paper, which discussed the mathematical models of neural networks, became the groundwork for future machine learning developments.
Machine learning can be used in almost any field with large data sets. These data sets and ML then make predictions or decisions. Companies like Yelp, Google, and Facebook employ machine learning to help acquire users, customer support, and fraud detection. ML careers include roles like data scientist and robotics engineer.
The World Economic Forum estimates that 97 million new jobs will be created from advances in technology — including AI — from 2020-2025. Experts in AI and ML may be in-demand as companies and careers shift toward new technologies.
Individuals interested in creative problem-solving, modeling, and programming can thrive in the ML industry. Graduates of ML master's programs can pursue related careers and may have a competitive advantage against candidates without related degrees. ML bootcamp graduates can also compete in the job market, but bootcamps have a limited scope and timeframe compared to master's degrees.
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Career Opportunities: Experts expect AI and ML to grow rapidly over the next decade. Machine learning candidates can pursue various careers across industries. Graduates of an ML program can demonstrate their education and expertise in this field. -
Positive Impact: ML experts may work on projects with real-world benefits. Healthcare, farming, and emergency relief companies have all used AI to help people. -
Hands-On Experience: Professionals in machine learning can work directly to code and improve programs. Individuals interested in seeing their work come to fruition may enjoy careers in the field.
Popular Online Programs
Learn about start dates, transferring credits, availability of financial aid, and more by contacting the universities below.
What To Expect From Master's in Machine Learning Programs
Master's in machine learning programs prepare students to pursue careers in the growing AI field. Programs focus on teaching students about ML principles and how to incorporate technology into different fields.
Individuals pursuing master's in machine learning degrees can expect approximately 30 credit hours of courses over 1-3 years. Program tuition can range from $10,000-$80,000. Institutions offer many types of ML programs, including master's degrees in ML or degrees in AI with a concentration in ML.
Enrollees explore courses in machine learning, deep learning, and other technical and AI-related topics. Some master's degrees also require a capstone project or thesis paper.
Admission Requirements
Each master's in ML program has specific admission requirements, but candidates typically submit online applications, send official transcripts, and pay the relevant fees. Each applicant must hold a bachelor's degree, usually in a subject related to computer science. Individuals with GPAs of 3.0 GPA may receive preference in certain programs.
Programs may require GRE scores, and some schools set a minimum score of 320. Master degree prerequisites may include programming courses, math courses, or an understanding of the two.
Degree and Specialization Options
Individuals interested in attending a machine learning program can choose from a master's degree in ML, a combination degree in AI and ML, or a degree in AI with a concentration in ML. An attendee's program choice depends on the branch of AI they plan to focus on.
Students must also choose their preferred learning experience: online, in-person, or hybrid. Online students may have additional flexibility and asynchronous classes, while in-person students experience additional networking opportunities.
Popular Master's in Machine Learning Courses
Machine learning programs offer different curriculums but usually include core courses and electives. While coursework varies among programs, the following list includes some of the most common classes.
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Machine Learning: This introductory course covers ML theories and principles. Topics may include model selection, overfitting, and decision theory. -
Deep Learning: Deep learning refers to a subdivision of machine learning that attempts to copy the way a human thinks. This course explains the theory and uses of deep learning. -
Design and Analysis of Algorithms: Students can learn about the complexity of data and related issues in this course. Classes cover graphing algorithms, lower bounds, and recurrences. -
Computer Vision:Computer vision allows computers to comprehend objects in images and videos. Coursework discusses real-life applications of this technology, along with visual processing, edge detection, and image modeling.
How Much Will a Master's in Machine Learning Cost?
Costs for a master's in machine learning vary significantly and may extend from $10,000-$80,000. Tuition prices depend on factors like institution prestige, out-of-state fees, and course load.
Enrollees should also budget for living expenses such as housing, food, and transportation. University students can apply for financial aid such as scholarships, fellowships, and grants to help with tuition and living costs. The links below provide additional information on how to pay for a degree.
Jobs for Graduates With Machine Learning Degrees
Master of machine learning graduates can use their skill sets in various roles and industries. Machine learning experts can find employment in robotics, data roles, software development, and more. Professionals in this field can pursue further opportunities with additional education, professional certifications, and experience.
Data scientists use data sets to extract answers and insights. These employees often start with raw data and organize it into meaningful categories. Multiple industries, including finance, retail, and education, employ data scientists to collect and analyze data. Data scientists can use visualization programs to present their findings to executives.
Software developers design software, write code, and create programs. Software developers with ML experience can incorporate their knowledge into programs to analyze data and predict user behavior. These developers can work independently or within teams.
Machine learning engineers use ML for computers to solve issues and forecast possibilities. These engineers employ a combination of data and algorithms to allow computers to function with minimal human interference. Note: the salary data below applies to fewer than 50 respondents.
- Required Education: Bachelor's degree
- Average Annual Salary, July 2023: $126,690
- Job Outlook (2021-31): Not available
These engineers design and develop robotic systems in industries like healthcare, manufacturing, or aerospace to conduct repetitive or dangerous tasks. They may work with autonomous robots, which can benefit from AI and ML, to better manage tasks and navigate spaces.
- Required Education: Bachelor's degree
- Average Annual Salary, July 2023: $91,120
- Job Outlook (2021-31): Not available
Learn about start dates, transferring credits, availability of financial aid, and more by contacting the universities below.
Choosing a Master's in Machine Learning Program
Applicants researching institutions should consider multiple factors in their decision. The list below highlights some common elements for prospective students to explore.
- Accreditation: Accreditation indicates that a program or institution meets a certain standard. Schools and individual programs can receive accreditation, and a single accredited program or department at an institution does not mean that all programs within the school are accredited.
- Student-To-Teacher Ratio: A higher ratio represents more students per teacher in the university. A lower ratio can indicate smaller class sizes and more interactive time with professors.
- Cost/Financial Aid: Tuition and related fees can vary significantly between programs. A university's scholarships or financial aid may also vary.
- Location: In-state students usually pay less than out-of-state students. People who live near universities can also save on rent and living expenses.
- Reputation: Prestigious institutions have more name recognition and larger alumni networks. Graduates from these universities may have more career opportunities.
Should You Study Machine Learning Online?
According to the National Center for Education Statistics, 60.1% of students in the 2020-2021 school year attended at least one online course in their postsecondary education. Master's in machine learning programs can translate especially well to online learning due to its subject matter. Students taking online machine learning courses can learn, program, and test theories simultaneously.
Not everybody equally enjoys the online learning experience. Prospective online enrollees should consider their self-motivation, ideal learning style, and the importance of communicating face-to-face with students and professors.
Learn about start dates, transferring credits, availability of financial aid, and more by contacting the universities below.
Questions About Master's in Machine Learning Degrees
What can you do with a master's in machine learning degree?
Individuals with a master's in machine learning can pursue careers such as data scientist, software developer, or AI engineer. Companies from different industries employ machine learning experts to solve complex issues.
Is a master's in machine learning worth it?
AI and ML are growing fields with career opportunities in multiple sectors. Individuals interested in technology and pursuing a career in AI/ML may find a master's in machine learning worth the cost.
Is a master's in machine learning hard?
Attendees of a master's in machine learning program should have technological and mathematical skills. Individuals that excel in these areas should find machine learning no harder than other technical programs.
How long does it take to get a master's in machine learning?
Machine learning programs have various courses and timelines. A master's in machine learning can take 1-3 years to complete.
Last reviewed June 26, 2023.
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