Written By - Brandon Mario D'Souza

Edited By Arlene Ward

Review & Contribution By Dr. Kristi Pratt

Since the world invented computers, their usage in everyday life has grown exponentially. And in the relatively recent past, businesses and organizations started using computers on datasets to gain intelligence from that data. And they do that by ‘training’ the machine on smaller data and applying that knowledge to larger or more data. That’s Machine Learning. And it is increasingly in demand because of the power it presents. This field generates a lot of buzz, encouraging individuals to pursue a Master’s in Machine Learning Online. Machine Learning is a subset of Artificial Intelligence, and it is about the application of actionable intelligence, where machines make decisions affecting how a product or a service behaves. According to the Bureau of Labor Statistics 1 , the skill requirement for computer and information research scientists is predicted to grow 23 percent from 2022 to 2032, faster than average for all occupations.

Masters in Machine Learning Online

Table Of Contents

Featured Online Programs

Southern New Hampshire University

PROGRAM: Online Masters Degrees

Southern New Hampshire University is a private, nonprofit, accredited institution with more than 3,000 on-campus students and over 60,000 online students, making us one of the fastest-growing universities in the country. Founded in 1932, we’ve been relentlessly reinventing higher education ever since and have gained national recognition for our dedication to helping students transform their lives and the lives of those around them.

We’re proud to provide affordable, accessible education that students can pursue on our 300-acre campus in Manchester, NH, over our innovative online platform or at our regional centers in Manchester, Nashua, Portsmouth and Salem, NH, and Brunswick, ME.

SNHU has earned the GetEducated.com Best Buy and Best of Business – Best Online Degree awards and is consistently ranked as a top Military Friendly® School by G.I Jobs®.

Best Master’s in Machine Learning Online Programs

Before choosing a master’s in machine learning online program, it is essential to vet different programs for their quality, affordability, and success rates. In this guide, we created a list of the best schools for machine learning. The following list of best graduate programs in machine learning universities is created, considering factors like research areas, research focus, honors, awards, job prospects, affordability, graduation rates, etc.:

<a href="https://www.onlinemasterscolleges.com/masters-in-machine-learning-online/">Master's in Machine Learning Online</a>

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College Name & AddressTuitionGraduation Rate
University of North Carolina, Chapel Hill
103 South Bldg Cb 9100, Chapel Hill, North Carolina 27599
Georgia Tech
225 North Ave, Atlanta, Georgia 30332
CSU Global
585 Salida Way, Aurora, Colorado 80011
Penns State University
201 Old Main, University Park, Pennsylvania 16802
Columbia University
West 116 St and Broadway, New York, New York 10027
Duke University
103 Allen Bldg, Durham, North Carolina 27708
Carnegie Mellon University
5000 Forbes Avenue, Pittsburgh, Pennsylvania 15213
Stevens Institute of Technology
Castle Point On Hudson, Hoboken, New Jersey 07030
Drexel University
3141 Chestnut St, Philadelphia, Pennsylvania 19104
University of Rochester
Wilson Blvd. – Wallis Hall, Rochester, New York 14627

Source – Integrated Post Secondary Education Data System & University Data
*Tuition rates are for in-state and per year. Program specific rates may apply.
**NA – data not available

Curriculum and Skills Gained in Machine Learning Programs

Many companies are ramping up their workforce to take advantage of concepts of Machine Learning, Artificial Intelligence, Big Data, and other similar topics to leverage their businesses. Enrolling in a machine learning online course is essential to be in tandem with the job market requirements and steer a career to a better place. A Masters in Machine Learning online program can help understand the theory and practical applications of all these techniques in detail. During the degree, understand and implement techniques like regression, supervised clustering, naïve Bayes, etc. While the curriculum from program to program can be different, some courses within the degree program are common. Here are some courses one can expect to see as part of a machine learning master’s online:

Introduction to Machine Learning

This course provides a foundational understanding of key concepts and algorithms in machine learning. Students explore supervised and unsupervised learning, model evaluation, and feature engineering. The course sets the stage for advanced topics, equipping learners with essential skills for subsequent coursework and real-world applications.

Foundational and in-depth concepts of Machine Learning

This course explores core principles and advanced techniques. Covering topics such as algorithms, model optimization, and ethical considerations, it equips students with a comprehensive understanding of machine learning, preparing them for sophisticated applications and research in the field.

Predictive Analytics 

This course includes various statistical techniques, including multiple regression, logistic regression, discriminant analysis, generalized linear models, and Cox proportional hazards regression. Students utilize R software to implement these methods on authentic datasets. Additionally, a collaborative project entails predictive modeling for a substantial dataset, fostering practical application skills.

Introduction to Databases & Information Retrieval

This course explores the fundamental principles of databases and techniques for effective information retrieval. Covering database design, query optimization, and search algorithms, it equips students with essential skills for managing and extracting valuable insights from vast datasets in machine learning applications.

Data Visualization

This course equips future analytics and data science professionals with practical skills to effectively visualize data and craft compelling narratives. Covering visualization rules, psychology, and storytelling, students learn to create powerful data stories and when to innovate within the visualization process.

Upon successfully completing this program, students will acquire the following skills and learning outcomes:

  •  Proficiency in machine learning algorithms
  •  Data preprocessing and feature engineering skills
  •  Model evaluation and optimization techniques
  •  Advanced statistical and mathematical concepts application
  •  Programming proficiency in languages like Python or R
  •  Understanding of deep learning principles
  •  Practical experience in real-world machine learning projects
  •  Ethical considerations in machine learning applications

Masters in Machine Learning Online Program Degree Types

Masters in Machine Learning Online is mainly offered as a Masters of Science in Machine Learning – MS in Machine Learning. Or it can be offered as a subset of an MS in Data Science. Some universities offer Machine Learning as a concentration within an MS in Computer Science.

Artificial Intelligence and Machine Learning

Machine Learning runs on the concept that machines should be able to learn from the existing data and adapt through experience. Whereas Artificial Intelligence enables a machine to analyze and perform actionable tasks – similar to the human being. The following are the prime differences between AI and ML:

Artificial IntelligenceMachine Learning
Creating intelligent machines to mimic human behavior
Developing machines that can solve complex problems
Machine Learning and Discipline Learning are subsets of AI
Automatically learning from the previous data to give accurate output
With no explicit program, it automatically learns from previous data
Discipline Learning is a subset of A

Some universities offer online masters in AI and ML. Here are some universities that offer these dual programs:

Machine Learning is a subset of Artificial Intelligence and a part of Data Science. Data Science is a broader aspect that blends the concepts of statistics, technical skills, and business vision to predict results. Machine Learning is based on Data Science for focusing and calculating algorithms and statistics of the given data to analyze the situation. Combining Machine Learning and the following programs will enhance skills and bring better career opportunities.

Area of FocusDescriptionCareers This Concentration Prepares For
Data AnalyticsThis specialization focuses on extracting actionable insights from diverse datasets. Students learn advanced techniques, statistical methods, and data visualization to make informed decisions and drive business value through effective analysis.Data AnalystsBusiness Intelligence AnalystsData Engineers
Artificial Intelligence (AI)This specialization explores advanced AI algorithms, machine learning, and deep learning. Students acquire expertise in developing intelligent systems, natural language processing, computer vision, and autonomous agents, preparing them for impactful roles in AI research and application development.Machine Learning EngineersAI Research ScientistsNatural Language Processing Engineers
Data ScienceThis specialization focuses on advanced analytics, statistical modeling, and machine learning techniques. Students gain expertise in extracting meaningful insights from complex data sets, making data-driven decisions, and contributing to the growing field of data science innovation.Data ScientistsStatisticiansData Architects
Predictive AnalyticsThis specialization explores advanced data modeling and machine learning techniques. Students acquire skills to analyze historical data, build predictive models, and make informed forecasts, enabling them to contribute to data-driven decision-making and strategic planning in various industries.Predictive ModelersRisk AnalystsOperations Analysts
Deep LearningThis specialization offers an in-depth exploration of advanced neural network techniques. Students explore complex topics such as convolutional and recurrent neural networks, reinforcement learning, and natural language processing, equipping them with specialized skills for cutting-edge applications in machine learning.Deep Learning EngineersNeural Network DevelopersComputer Vision Specialists

Online Master’s in Machine Learning Program Length

A professional seeking a Machine Learning course may be interested in the duration it takes to complete the program. Many factors go into determining the length of the programs, given that there are several parameters like full-time, part-time, how many credits per semester, background, and more. Most students will graduate from a program for a master’s in machine learning in about two years.

Accelerated Machine Learning Programs

Accelerated master’s programs in Machine Learning offer a streamlined path for students to complete their degree efficiently. These programs cater to motivated and dedicated students aiming to expedite their studies and graduate earlier. To expedite their progress, students can accelerate their program by opting for an increased course load, including summer or intensive courses. Additionally, they may be able to transfer credits from prior coursework or relevant professional experiences, reducing the overall time needed to complete the Machine Learning degree.

Master’s in Machine Learning Online Admission Requirements

Universities offering masters in machine learning online are seeing a lot of footprints and applicants coming by to enroll in the online program. But, during this process, many forget to check the admission requirements before applying to delay the enrolment process. So, it is better to have a checklist of admission requirements and prepare accordingly:

  • Bachelor’s Degree: A completed undergraduate degree in a related field such as computer science, engineering, mathematics, or a relevant discipline.
  • Academic Transcripts: Submission of official academic transcripts from all previous institutions attended.
  • Letters of Recommendation: Typically, two or more letters of recommendation attesting to the applicant’s academic and/or professional qualifications.
  • Statement of Purpose: A written statement outlining the applicant’s academic and career goals and reasons for pursuing a Master’s in Machine Learning.
  • Resume/CV: A detailed resume or curriculum vitae highlighting relevant work experience, projects, and skills.
  • Standardized Tests: Some programs may require GRE scores. Check specific program requirements.
  • Programming Proficiency: Demonstrated proficiency in programming languages commonly used in machine learning, such as Python or R.
  • Work Experience (Optional): Some programs may consider relevant work experience a factor in admission.
  • Interview: Some programs may require an interview as part of the admission process.

No GRE Master’s in Machine Learning Online Programs

The (Graduate Record Examination (GRE) and Graduate Management Admission Test (GMAT) are commonly used standardized tests for graduate program admission. While many U.S. schools often require these scores, some online master’s programs in Machine Learning may not demand a GRE or GMAT. Waiving this requirement recognizes that standardized test scores may not predict an applicant’s success consistently. Colleges may instead emphasize factors like academic background, research experience, statement of purpose, letters of recommendation, and interviews. Prospective students pursuing an online master’s in Machine Learning should contact their chosen universities’ Machine Learning departments to explore programs without GRE requirements or options for obtaining a waiver.

Accreditation for Master’s in Machine Learning Online Programs

Accreditation ensures that a university meets specific educational standards, guaranteeing the quality of its programs. For students, choosing an accredited university for a Master’s in Machine Learning is crucial because accreditation affirms the program’s legitimacy, faculty competence, and academic resources. Besides, accredited programs are recognized and valued by potential employers. The Artificial Intelligence Board of America (ARTiBA)5 (ARTiBA) is one of the primary accreditation bodies that confirms if the university/college follows the quality benchmark in learning, teaching, and researching Artificial Intelligence and Machine Learning

Universities can also be accredited nationally or by one of six regional accrediting agencies:

Read more about accreditation in the Accreditation Guide.

Where to Find Free Online Courses for Master’s in Machine Learning Students

In the field of machine learning, students can register for free courses to deepen their comprehension of the field. Some of these free courses provide insights into professional practices within the domain. Upon successful completion, participants may be awarded certificates of completion. It’s crucial to recognize that while these certificates acknowledge completion, they may not carry the same weight as accredited courses. Below are examples of free machine learning courses:

Artificial Intelligence and Machine Learning in Business6

In this course, students learn about the paramount significance and applications of artificial intelligence (AI) in contemporary times. AI has transformed societies and economies, enhancing human labor’s speed, efficiency, and precision across various fields such as robotics, fraud detection, and online commerce. The course is crafted to cultivate awareness among computer specialists and individuals new to the field but keen on pursuing a career in AI. It provides an introduction to the fundamentals of AI and its subsets.

  • Provided by – Alison

Machine Learning for Research7

The course commences with an overview of the specific applications of machine learning in the scientific process. It imparts understanding not only of the potency of machine learning but also discerns situations in which its application to scientific research is suitable (or unsuitable).

  • Provided by – Udemy

Machine Learning8

In this course, students learn about Supervised Learning, a machine learning task enabling voice recognition on phones, spam filtering in emails, and various other applications. The second part delves into Unsupervised Learning, exploring how platforms like Netflix and Amazon predict preferences and needs based on user behavior.

  • Provided by – Class Central

How to Pay for Machine Learning Programs?

Machine Learning has become the favorite subject of professionals and students alike, and many look forward to enrolling in Machine Learning programs according to each one’s convenience. However, the primary question students would always have is the process of paying for the program. Many universities offer some kind of financial assistance to students. There are  many other ways to pay for higher education, like – employer reimbursed tuition, student loans, fellowships, grants, etc.


Scholarships are financial aid awarded based on academic, extracurricular, or demographic criteria. They recognize achievements and talents, providing opportunities for individuals to pursue their academic goals without significant financial constraints.


Grants are financial aid typically awarded based on financial need or specific criteria. Like scholarships, Grants do not require repayment, providing financial assistance to individuals pursuing education, research, or projects, contributing to societal development and personal growth.

Graduate Assistantships

Graduate Assistantships involve students working part-time in academic or research roles while pursuing their graduate studies. In exchange, they receive tuition waivers or stipends, helping to offset educational costs. This experience provides practical skills, networking opportunities, and financial support for graduate students, enhancing their academic journey.

Student Loans

Student loans are borrowed funds to cover educational expenses. They must be repaid with interest after completing their studies. While they help finance education, students should carefully consider loan terms, interest rates, and repayment plans. Student loans provide financial support but require responsible management to avoid long-term financial burdens.


FAFSA, or Free Application for Federal Student Aid, is a crucial form for students seeking financial assistance for higher education. By completing FAFSA, individuals become eligible for federal grants, loans, and work-study programs, facilitating access to crucial financial support.

Read more about financial assistance in the best finance guide.

Scholarships for Machine Learning Students

Apart from student loans or other financial aid forms, it would greatly help if the program is conferred on a scholarship. The grant of an award encourages an enthusiastic and deserving candidate in enrolling for the Master’s program and pursue it comfortably. Here is a list of some scholarship awards that are available for machine learning students, which include some fellowships that will bolster student’s experience:

Simplr Artificial Intelligence and Technology Scholarship9

Simplr, a company offering customer service solutions to e-commerce firms, seeks to encourage and assist students in technical disciplines. The organization offers scholarships to those pursuing an undergraduate or graduate degree in Computer Science, Mathematics, or Information Technology. Applicants must submit an essay on topics such as Artificial Intelligence and Machine Learning, The Internet of Things (IoT), or Blockchain Technology.

  • Award Amount: $7,500 
  • Deadline: Varies

Google Lime Scholarship10

The Google Lime Scholarship Program aids students with disabilities pursuing degrees in computer science or related fields. Awardees receive financial support, mentorship from Google, and networking opportunities. The initiative strives to foster diversity and inclusion within the tech industry.

  • Award Amount: $10,000 
  • Deadline: April every year

Association for the Advancement of Artificial Intelligence11

The Association for the Advancement of Artificial Intelligence (AAAI) offers scholarships to support students pursuing studies or research in artificial intelligence. These scholarships aim to foster talent and innovation in AI-related fields, providing financial assistance and recognition to exceptional students and contributing to advancing artificial intelligence research and applications.

  • Award Amount: Varies
  • Deadline: December every year

Careers and Salary Outlook for Machine Learning Graduates

The concepts of Machine Learning and AI are penetrating the markets at an unprecedented speed. Today, most companies looking for a thriving business are slowly transforming by adopting Machine Learning in one form or another. According to Indeed report 201912, Machine Learning Engineer stands first (#1) in the list of The Best jobs in the US, showing a 344% growth with a median salary of $146,085 per year. Here are other career choices that one can make by enrolling in a Master’s in Machine Learning:

Job TitleAverage SalaryJob Growth (up to 2032)Job Description
Machine Learning Engineer13$123,151No Data AvailableBuilding and managing programs for machine learning projects 
Data Scientist14$99,606No Data AvailableCollect, analyze, and interpret large complex datasets by leveraging both machine learning and predictive analytics
Business Intelligence Developer15$86,165No Data AvailableAnalyze complex datasets to identify business and market trends
Machine Learning Researcher16$144,871No Data AvailableA researcher in machine learning develops and implements contemporary methods such as artificial intelligence, statistical techniques, and various algorithms (clustering, classification, deep learning, transfer learning, adversarial learning, active learning, continuous learning, explanation learning, etc.) to extract patterns and models from industrial data. This involves collaborating with senior researchers and multidisciplinary teams to address supervised and unsupervised learning challenges within an applied research setting.

Certifications and Licensing for Online Master’s Students in Machine Learning

Certification serves as a formal acknowledgment of one’s skills meeting the necessary standards, while licensing is an official permit granted by an authorized agency, confirming eligibility to utilize one’s skill set for personal or professional purposes. Both certification and licensing empower individuals to apply their expertise effectively. Several agencies provide machine learning certification and licensing options. Below is a list of reputable machine learning certification  programs:

AWS Certified Machine Learning17

AWS Certified Machine Learning is for individuals with over a year of experience developing, architecting, or managing machine learning/deep learning workloads in the AWS Cloud. Prerequisites include a minimum of two years of hands-on experience, proficiency in expressing basic Machine Learning algorithms’ intuition, performing basic hyperparameter optimization, familiarity with ML and deep learning frameworks, and adhering to model training, deployment, and operational best practices.

Google Professional Machine Learning Engineer Certification18

Google Professional Machine Learning Engineer Certification validates individuals with expertise in designing, building, and deploying machine learning models on the Google Cloud Platform. This certification affirms the ability to design highly expandable and reliable ML systems, making candidates proficient in creating impactful solutions and optimizing models for production efficiency.

The Certified Artificial Intelligence Professional (CAIP)19

The Certified Artificial Intelligence Professional (CAIP)™ equips individuals with a strong understanding of AI principles, covering logic, knowledge representation, random models, and machine learning. Designed to clarify AI complexities, the program explores terminology, potential applications, and ethical considerations. It accommodates all experience levels, offering flexibility in scheduling and fostering skills in machine learning, data science, team collaboration, and strategic implementation.

Additional Resources for Machine Learning Professionals

Associations, communities, conferences, and exhibitions provide opportunities to network with peers. Although individuals cannot be linked in a commonplace, a shared interest (Machine Learning) keeps them associated with each other. These channels assist both professionals and students in staying updated on global changes in Machine Learning concepts. Here are some associations/communities formed for Machine Learning enthusiasts and followers:

  • International Machine Learning Society (IMLS) : The IMLS is a non-profit organization whose main aim is to foster machine learning research and whose main activity is coordinating the annual International Conference on Machine Learning (ICML).
  • INFORMS : INFORMS is the leading international association for operations research and analytics professionals.
  • Partnership on AI : The Partnership on AI conducts research, facilitates discussions, shares insights, offers thought leadership, collaborates with relevant third parties, addresses public and media inquiries, and develops educational material to enhance the comprehension of AI technologies. This includes machine perception, learning, and automated reasoning.
  • Security Industry Association (SIA) : SIA advocates for non-regulatory approaches that promote AI research and development, empowering security professionals to leverage new capabilities for enhanced effectiveness in security and life safety systems.

FAQs About the Master’s in Machine Learning Online Program

Frequently Asked Questions

What is a Master’s in Machine Learning?

A Master’s in Machine Learning is an advanced academic program focused on developing expertise in the theories, algorithms, and applications of machine learning—an integral part of artificial intelligence. Students gain a deep understanding of data-driven modeling, pattern recognition, and statistical techniques, preparing them for impactful roles in AI research and industry applications.

How long does it take to complete a Master’s in Machine Learning?

Is an Online Master’s in Machine Learning worth it?

How important is program accreditation in choosing an online Master’s in Machine Learning?

What can you do with an Online Master’s in Machine Learning degree?

Is it necessary to have a Bachelor’s Degree in Machine Learning to pursue a master’s?

Can I pursue a Master’s in Machine Learning online while working?


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