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, 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.
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Featured Online Master’s Programs
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Southern New Hampshire University
PROGRAM: Best & Affordable Online Masters Programs
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®.
10 Best Masters 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.:
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University of North Carolina, Chapel Hill
The University of North Carolina at Chapel Hill’s online Master of Applied Data Science (MADS) delivers a future-focused curriculum to prepare professionals for real-world data challenges. Recognized by Fortune Education as a top online data science program, this degree blends technical expertise with ethical considerations, ensuring graduates can collect, process, analyze, and interpret data for impactful decision-making. The program integrates hands-on experience with industry collaboration, advanced programming, and machine learning applications. With interdisciplinary faculty from biostatistics, computer science, and mathematics, this flexible, 16-month program equips professionals to drive innovation in business, government, and society through data-driven solutions.
Tuition: $10,552
Graduation Rate: 91%
Address: 103 South Bldg Cb 9100, Chapel Hill, North Carolina 27599
Georgia Tech
Georgia Tech’s Online Master of Science in Computer Science (OMSCS) revolutionizes access to advanced computing education with a flexible, affordable, and rigorous curriculum. This highly ranked program offers the same world-class faculty and coursework as the on-campus degree, empowering students to specialize in Machine Learning, Interactive Intelligence, Robotics, and Computing Systems. Designed for working professionals, OMSCS delivers high-quality instruction through Georgia Tech’s renowned College of Computing. With tuition significantly lower than traditional programs and the ability to study from anywhere, this program enables ambitious professionals to elevate their expertise and advance their careers in cutting-edge computing fields.
Tuition: $14,064
Graduation Rate: 90%
Address: 225 North Ave, Atlanta, Georgia 30332
Columbia University
Columbia University’s Computer Science Master’s Degree delivers a rigorous and flexible curriculum for those seeking to excel in cutting-edge technology fields. With specialized tracks in Machine Learning, Artificial Intelligence, Cybersecurity, and Software Systems, the program prepares students to tackle real-world challenges in industries such as finance, healthcare, and intelligent systems. Courses are taught by world-renowned faculty and emphasize both foundational knowledge and emerging innovations. The program offers the option to study fully online, making it accessible to professionals worldwide. With strong industry connections and a proven track record of success, this degree will unlock opportunities in top-tier tech careers.
Tuition: $53,576
Graduation Rate: 95%
Address: West 116 St and Broadway, New York, New York 10027
Eastern University
Eastern University’s MS in Data Science delivers an affordable, self-paced, 100% online program for career advancement in one of today’s most in-demand fields. With a curriculum focused on industry-standard tools like Python, R, SQL, Tableau, and AWS, this program equips students with essential programming, machine learning, and data analysis skills. Recognized as a top-ranked online data science master’s program, it offers flexibility with seven-week course sessions and completion in as little as 10 months. Whether transitioning into data science or enhancing existing expertise, this degree provides the knowledge and credentials to thrive in a data-driven economy.
Tuition: $14,416
Graduation Rate: 56%
Address: 1300 Eagle Rd, Saint Davids, Pennsylvania 19087-3696
George Washington Institute of Technology
The George Washington Institute of Technology’s Online Master of Engineering in Artificial Intelligence and Machine Learning delivers a rigorous, industry-focused curriculum to prepare students for careers in AI-driven fields. This program covers deep learning, neural networks, computer vision, and reinforcement learning and provides the technical expertise needed to develop intelligent systems and cutting-edge AI applications. With a flexible, 100% online format, students gain hands-on experience while balancing professional commitments. Emphasizing both innovation and ethical considerations, this degree equips graduates with the skills to excel in technology, finance, healthcare, and beyond—ensuring a competitive edge in the evolving world of artificial intelligence.
Tuition: $35,100
Graduation Rate: 85%
Address: 1918 F Street, NW, Washington, District of Columbia 20052
Carnegie Mellon University
Carnegie Mellon University’s Master of Science in Machine Learning is an elite program for those seeking to master AI’s mathematical and computational foundations. With rigorous coursework in deep learning, probabilistic graphical models, optimization, and advanced statistics, this program delivers the skills to solve real-world machine-learning challenges. The curriculum combines theoretical depth with hands-on experience through electives and a required practicum, ensuring that graduates are prepared for research, industry innovation, or doctoral studies. Backed by a world-renowned faculty and a legacy of AI leadership, this program is a gateway to cutting-edge careers in artificial intelligence.
Tuition: $48,496
Graduation Rate: 93%
Address: 5000 Forbes Avenue, Pittsburgh, Pennsylvania 15213
Colorado State University Global
Colorado State University Global’s Online Master of Science in Artificial Intelligence and Machine Learning is designed for those eager to master the future of technology. With programming, AI, machine learning, and computer vision courses, this program equips students with the skills to develop intelligent systems and solve real-world challenges. Offering a flexible online format allows working professionals to gain advanced expertise while balancing career commitments. Ranked among the top AI programs, this degree provides a competitive edge in a rapidly evolving industry, preparing graduates for high-paying research, engineering, and software development roles.
Tuition: $9,000
Graduation Rate: Not Mentioned
Address: 585 Salida Way, Aurora, Colorado 80011-0000
Stevens Institute of Technology
Stevens Institute of Technology’s Applied Artificial Intelligence Master’s Program delivers cutting-edge training in AI, machine learning, and data-driven decision-making. Designed for those seeking advanced expertise in intelligent systems, computer vision, NLP, and robotics, this program blends theoretical foundations with hands-on applications. Located near New York City’s thriving tech hub, students gain access to top industry leaders, research opportunities, and career placement resources. With flexible online options, state-of-the-art labs, and a curriculum aligned with industry demands, graduates are well-prepared for high-impact AI engineering, data science, and business intelligence roles across major companies like Amazon, Bloomberg, and Microsoft.
Tuition: $41,380
Graduation Rate: 90%
Address: Castle Point On Hudson, Hoboken, New Jersey 07030
Drexel University
Drexel University’s Master’s in Machine Learning and Artificial Intelligence delivers a rigorous, interdisciplinary curriculum to meet the growing demand for AI expertise. With a strong foundation in mathematical principles, algorithms, and real-world applications, this program equips graduates for leadership roles in AI-driven industries. A flexible curriculum offers computational and applied tracks, allowing specialization in big data analytics, computer vision, and human-computer interaction. The quarter-based system provides a fast-paced learning environment, while hands-on capstone projects and co-op opportunities enhance industry readiness. Located in Philadelphia’s tech hub, Drexel fosters strong industry connections, leading to career opportunities at top global companies.
Tuition: $36,324
Graduation Rate: 77%
Address: 3141 Chestnut St, Philadelphia, Pennsylvania 19104
Northeastern University
Northeastern University’s Master of Professional Studies in Applied Machine Intelligence blends AI, machine learning, and data-driven decision-making to prepare graduates for leadership in an evolving technological landscape. With a multidisciplinary approach, the program emphasizes experiential learning through industry partnerships with global companies like Google, Deloitte, and Uber. Practical coursework in data management, visualization, and AI applications builds expertise for solving real-world challenges. Focusing on ethical AI, innovation leadership, and business strategy equips professionals to drive digital transformation. Flexible learning options and strong industry connections lead to success in AI-driven roles across diverse industries.
Tuition: $27,728
Graduation Rate: 90%
Address: 360 Huntington Ave, Boston, Massachusetts 02115-5005
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 Master’s in Machine Learning Online 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 Master’s in Machine Learning online program can help students understand the theory and practical applications of all these techniques in detail. During the degree, students 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
Master’s in Machine Learning Online Degree Types
Master’s in Machine Learning Online is mainly offered as a Master’s 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 Intelligence | Machine 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 AI |
Some universities offer online masters in AI and ML. Here are some universities that offer these dual programs:
Concentrations and Related 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 Focus | Description | Careers This Concentration prepares for |
|---|---|---|
| Data Analytics | This 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 Analysts • Business Intelligence • Analysts • Data 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 Engineers • AI Research Scientists • Natural Language Processing Engineers |
| Data Science | This 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 Scientists • Statisticians • Data Architects |
| Predictive Analytics | This 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 Modelers • Risk Analysts • Operations Analysts |
| Deep Learning | This 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 Engineers • Neural Network Developers • Computer Vision Specialists |
Master’s in Machine Learning Online 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 Master’s in Machine Learning Online 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) (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:
- New England Commission of Higher Education (NECHE)
- Middle States Commission on Higher Education (MSCHE)
- Higher Learning Commission (HLC)
- Southern Association of Colleges and Schools Commission on Colleges (SACSCOC)
- Northwest Commission on Colleges and Universities (NWCCU)
- Western Association of Schools and Colleges (WASC) Senior College and University Commission (WSCUC)
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:
| Course | Description | Provided by |
|---|---|---|
| Artificial Intelligence and Machine Learning in Business | 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. | Alison |
| Machine Learning for Research | 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). | Udemy |
| Machine Learning | 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. | Class Central |
How to Pay for Master’s in Machine Learning Online 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
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
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
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 Scholarship
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 Scholarship
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 Intelligence
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 2019, 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 Title | Average Salary | Job Growth (up to 2032) | Job Description |
|---|---|---|---|
| Machine Learning Engineer | $123,151 | No Data Available | Building and managing programs for machine learning projects |
| Data Scientist | $99,606 | No Data Available | Collect, analyze, and interpret large complex datasets by leveraging both machine learning and predictive analytics |
| Business Intelligence Developer | $86,165 | No Data Available | Analyze complex datasets to identify business and market trends |
| Machine Learning Researcher | $144,871 | No Data Available | A 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 Learning
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 Certification
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)
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
What is a Master’s in Machine Learning?
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?
Will Employers Want to See an On-Campus Master’s Degree in Machine Learning?
What is the difference between a master’s in AI and machine learning and a graduate certificate in AI and machine learning?
What skills will I gain from the Machine Learning Master’s program?
Are Online Master’s Degrees in Machine Learning as Valuable as In-Person Degrees?
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