- 1.Hakia's analysis of the best online machine learning degree programs reveals that mL Engineers earn a median salary of $157,000 with 40% projected job growth through 2032 (BLS OES 2024)
- 2.Top-ranked Machine Learning programs include University of Washington-Seattle Campus, Carnegie Mellon University, Syracuse University based on graduation rates, program strength, and career outcomes
- 3.Best value: University of Washington-Seattle Campus offers machine learning education at $11,524/year with 97% graduation rate
- 4.50 accredited Machine Learning programs analyzed using IPEDS 2023 completion data
Best Machine Learning Programs - Top 10 Online
University of Washington-Seattle Campus
UW's engineering-focused AI/ML program is uniquely designed as a stackable degree system where working engineers can earn certificates that build toward a master's, with Boeing Company funding support and specializations spanning everything from robotics to materials science.
University of Washington-Seattle Campus Machine Learning Program Overview
Hakia ranks University of Washington-Seattle Campus as the #1 in machine learning degree program.
The University of Washington-Seattle Campus offers two distinct machine learning pathways: the Master of Science in Artificial Intelligence and Machine Learning for Engineering and the Master of Science in Data Science. The AI/ML for Engineering program is a flexible, stackable degree launching Fall 2026 that's specifically designed for working engineers who want to apply AI and ML to physical systems like manufacturing, robotics, and chemical processes. Built with Boeing Company funding support, this program can be completed fully online part-time or as a full-time student, combining foundational AI/ML skills with domain-specific training across multiple engineering disciplines. The complementary MSDS program has been operating since earlier and focuses on professional data science careers, meeting evenings on campus with an industry-relevant curriculum covering statistical modeling, data visualization, and software engineering. Both programs leverage UW's position as a top-10 global university with deep Seattle tech industry connections.
Hakia Insight: University of Washington-Seattle Campus graduates earn $165,000, driven by the program's industry connections and hands-on machine learning curriculum.
Degree Programs
Research Labs & Institutes
Real-time learning and control of complex dynamic systems
Data-driven discovery and control of dynamical systems
Data-intensive discovery across all fields using large, complex datasets
Scale-independent Multimodal Automated Real Time Systems
Location Advantages
- •Adjacent to Seattle tech ecosystem: Google, Amazon, Microsoft, Meta all have major R&D presence
- •Access to leading independent AI research (Allen Institute for AI)
- •Strong startup community and venture capital activity
Industry Partners
Career Outcomes
Certifications & Designations
Admissions
Carnegie Mellon University
CMU houses the world's first academic machine learning department, founded in 2006, and has maintained the #1 ranking in artificial intelligence since 1997 according to U.S. News & World Report.
Carnegie Mellon University Machine Learning Program Overview
Hakia ranks Carnegie Mellon University as the #2 in machine learning degree program.
Carnegie Mellon's Master's in Machine Learning program emerges from the world's first academic machine learning department, founded in 2006. This intensive 16-month program can be completed in three semesters by motivated students, though many take four semesters to deepen their research experience or strengthen foundational skills. The curriculum demands six rigorous core courses spanning probabilistic graphical models to optimization theory, three specialized electives, and a full-time summer practicum that often leads to coveted industry positions. Students work alongside faculty who literally wrote the textbooks on machine learning, with access to cutting-edge research labs studying everything from deep reinforcement learning to AI ethics. The program welcomes students from diverse academic backgrounds - computer science majors study alongside physics PhDs and mathematics graduates - united by exceptional analytical skills and programming proficiency.
Hakia Insight: Carnegie Mellon University leverages partnerships with Amazon and Bosch Group to offer students real-world project experience valued by employers.
Degree Programs
Research Labs & Institutes
World's first academic ML department with research spanning theoretical foundations to real-world applications
Industry Partners
Career Outcomes
Certifications & Designations
Admissions
Syracuse University
Syracuse University's iSchool has been pioneering information science education since 1928 and uniquely integrates human-centered design principles into AI education, ensuring graduates develop both cutting-edge technical skills and ethical frameworks for responsible AI deployment.
Syracuse University Machine Learning Program Overview
Hakia ranks Syracuse University as the #3 in machine learning degree program.
Syracuse University's machine learning and AI programs are housed within the innovative School of Information Studies (iSchool), which offers a distinctive interdisciplinary approach combining technology with human-centered design. The flagship Master of Science in Applied Human-Centered Artificial Intelligence is a 31-credit, on-campus program that can be completed in as little as one year, emphasizing hands-on projects and portfolio development. The program stands out for its focus on responsible AI development, featuring core courses in Natural Language Processing, Deep Learning in Practice, and Responsible AI. Students work in state-of-the-art facilities while engaging with faculty like Professor Wanliang Shan, who leads research in soft robotics and machine learning applications. The iSchool also offers a complementary MS in Applied Data Science (34 credits) with specialized tracks in AI, Big Data, and Visual Analytics, available both on-campus and online through their established distance learning platform.
Hakia Insight: Syracuse University's industry network — including NetApp and ADP — provides students with internship and hiring pathways.
Degree Programs
Research Labs & Institutes
Smart, Hybrid, Active and Nature-inspired Materials, Mechanics, and Machines with machine learning applications
Interdisciplinary research including AI applications in biomedical engineering
Location Advantages
- •Central New York region with healthcare and financial sector presence
- •Access to NYC and Boston tech hubs via proximity
- •Regional insurance and finance industry connections
Industry Partners
Career Outcomes
Certifications & Designations
Admissions
University of California-Irvine
Home to the world-famous UCI Machine Learning Repository with 688 datasets used by millions of researchers globally, plus the unique HPI Research Center partnership with Germany's leading tech institute launched in 2020.
University of California-Irvine Machine Learning Program Overview
Hakia ranks University of California-Irvine as the #4 in machine learning degree program.
UC Irvine's machine learning programs span multiple pathways through the Donald Bren School of Information and Computer Sciences, one of only five computing-focused schools among Association of American Universities (AAU) members. The flagship MS in Computer Science offers deep specialization in artificial intelligence and machine learning through its comprehensive core curriculum, with students choosing from seven specialized areas including the dedicated Artificial Intelligence track featuring courses like COMPSCI 273A Machine Learning. For professionals seeking applied expertise, the Master of Data Science (MDS) program provides both full-time and part-time options with industry-focused curriculum emphasizing experiential learning in statistical modeling, machine learning, data management, and AI. The school maintains over 688 datasets in the renowned UCI Machine Learning Repository, serving millions of researchers worldwide and providing students unique access to cutting-edge data resources.
With approximately 4,000 undergraduates, 600 master's students, and 400 doctoral students, the school creates an exceptional research environment supported by over 50 Computer Science faculty including 15 ACM Fellows, 13 IEEE Fellows, and 15 AAAS Fellows. Students benefit from the Center for Machine Learning and Intelligent Systems connecting more than thirty faculty across disciplines, plus specialized research centers like the Computational Vision Lab and the HPI Research Center in Machine Learning and Data Science established in 2020. The programs emphasize real-world application through industry capstone projects, with MDS students working directly on data science problems with corporate partners.
Hakia Insight: University of California-Irvine's HPI Research Center in Machine Learning and Data Science creates a direct research-to-career pipeline with Various industry partners, bridging academic research and industry practice.
Degree Programs
Research Labs & Institutes
Addresses challenges of the modern data-driven world, using computer algorithms to discover useful information from vast data archives
Partnership with Hasso Plattner Institute promoting research and educational activities in ML and data science
Understanding information processing capabilities of biological visual systems and developing computational systems for visual media
Maintains 688 datasets as a service to the machine learning community worldwide
Industry Partners
Career Outcomes
internet companies, finance, engineering, business, medicine
Admissions
University of Southern California
USC houses the MS in Computer Science - Artificial Intelligence, the first dedicated AI master's program in the United States, while its interdisciplinary approach uniquely combines machine learning with wireless communications, social impact applications, and entertainment industry connections in the heart of Los Angeles.
University of Southern California Machine Learning Program Overview
Hakia ranks University of Southern California as the #5 in machine learning degree program.
USC's Viterbi School of Engineering offers a comprehensive suite of machine learning and data science programs that bridge theoretical foundations with real-world applications. The flagship MS in Electrical and Computer Engineering - Machine Learning and Data Science provides focused, rigorous training in data science techniques, machine learning, and signal processing within the wireless communications domain. Complementing this is the MS in Computer Science - Artificial Intelligence, one of the nation's first dedicated AI master's programs, offering specialized tracks in deep learning, computer vision, natural language processing, and robotics. For students seeking broader data science foundations, the MS in Applied Data Science trains professionals from diverse backgrounds through hands-on experiences and a unique professional practicum, emphasizing practical skills in Python programming, database management, and big data infrastructure.
All programs require 32 units and can be completed in 1.5-2 years full-time. USC's machine learning ecosystem spans multiple research centers including the USC Center for Artificial Intelligence in Society, the Robotics and Autonomous Systems Center, and specialized labs like the Machine Learning and Data Mining Lab (Melady) and the Computational Social Science Laboratory. Students benefit from LA's tech corridor proximity and USC's extensive alumni network, with graduates placing at top-tier companies like Amazon, Google, Meta, and emerging AI startups.
Hakia Insight: Students at University of Southern California benefit from active collaborations with Amazon and Meta, connecting classroom learning to the workforce.
Degree Programs
Research Labs & Institutes
AI applications for social good including combating human trafficking and wildlife conservation
Advanced machine learning algorithms and data mining techniques
Human-robot interaction, socially assistive robotics, and multi-robot systems
Data science applications in social sciences and network analysis
Machine learning applications in wireless communications
Industry Partners
Career Outcomes
Amazon, Google, Microsoft, Apple, Intel
Admissions
Indiana University-Bloomington
IU's machine learning programs operate from the $35 million Luddy AI Center within the unique Mind, Brain, and Machine Quad, fostering unprecedented collaboration between AI researchers and cognitive scientists, psychologists, and neuroscientists.
Indiana University-Bloomington Machine Learning Program Overview
Hakia ranks Indiana University-Bloomington as the #6 in machine learning degree program.
Indiana University-Bloomington offers machine learning education through multiple pathways within the Luddy School of Informatics, Computing, and Engineering. The flagship program is the PhD in Intelligent Systems Engineering, which advances engineering using artificial intelligence, embedded computing, and sophisticated data interpretation. Students can also pursue machine learning through the MS in Computer Science, which explores AI, machine learning, and big data applications, or the comprehensive Data Science programs that include foundational machine learning coursework across five specialized tracks. The university's $35 million Luddy Artificial Intelligence Center, opened in 2021, serves as the hub for AI and machine learning research, bringing together over 60 faculty members from across the university in the Mind, Brain, and Machine Quad.
What sets IU apart is its interdisciplinary approach - the Luddy AI Center connects faculty from nearly every college, creating unique collaboration opportunities between computer science, psychology, cognitive science, and neuroscience. Students gain hands-on experience through practical projects and research early in their studies, with access to advanced cyberinfrastructure including Big Red 200, one of the fastest university-owned supercomputers in the country.
Hakia Insight: Indiana University-Bloomington's industry network — including IBM and Amazon — provides students with internship and hiring pathways.
Degree Programs
Research Labs & Institutes
Human-centered AI research spanning theoretical foundations to societal applications
Robot systems for navigation in difficult environments and emergency response
Personalized speech enhancement and recognition systems
Machine learning for detecting bias and hate speech on social platforms
Location Advantages
- •Midwest tech corridor
- •Proximity to Indianapolis healthcare and financial services companies
- •Regional startup ecosystem
Industry Partners
Career Outcomes
Certifications & Designations
Admissions
University of Pennsylvania
Penn's MSE-AI is taught by some of the top AI researchers in the world and uniquely emphasizes ethical AI training alongside technical rigor, preparing graduates not just to build AI tools but to responsibly shape the future of this transformative technology.
University of Pennsylvania Machine Learning Program Overview
Hakia ranks University of Pennsylvania as the #7 in machine learning degree program.
Penn Engineering's Master of Science in Engineering in Artificial Intelligence (MSE-AI Online) is a fully online, asynchronous program that equips students with both cutting-edge technical skills and robust ethical frameworks for AI development. Known as The Raj and Neera Singh Program in Artificial Intelligence, this degree covers classical AI, natural language processing, generative AI, and modern deep learning while preparing students to address AI's societal risks head-on. The program is designed for professionals with computer science or engineering backgrounds who want to stay ahead of industry demand while studying from anywhere in the world. Students benefit from Penn's world-renowned AI faculty and engage with real-world tools and environments through hands-on assignments, all while being part of a tight-knit online community supported by robust engagement platforms.
Hakia Insight: University of Pennsylvania's industry network — including AWS and Google — provides students with internship and hiring pathways.
Degree Programs
Research Labs & Institutes
Premier research center in robotics, vision, perception, control, and learning
AI-Enabled Systems: Safe, Explainable and Trustworthy
Network science, economics, sociology, and cryptography approaches to data
Innovation in Data Engineering and Science
Industry Partners
Career Outcomes
Admissions
University at Albany
UAlbany is one of the few universities to integrate topological data analysis as a core component of its data science curriculum, offering specialized training in this emerging field alongside traditional machine learning and statistics.
University at Albany Machine Learning Program Overview
Hakia ranks University at Albany as the #8 in machine learning degree program.
The University at Albany offers a Master of Science in Data Science that uniquely positions itself at the intersection of mathematics, machine learning, and cutting-edge topological data analysis. Housed in the Department of Mathematics within the College of Arts and Sciences, this program provides comprehensive training across three core areas: topological data analysis, machine learning, and statistics. Students gain hands-on experience with current industry tools including Python, R, TensorFlow, and specialized topological data analysis software like Ayasdi's Mapper, Eirene, and Ripser.
The program features a flexible curriculum structure with core requirements, specialized tracks, and practical components including comprehensive data analysis projects with oral presentations. Students can tailor their learning path through electives and practicum courses in either topological data analysis or machine learning. The program is designated as STEM, offering international students extended Optional Practical Training opportunities of up to 36 months. UAlbany also offers a unique 4+1 accelerated option for current undergraduates, allowing completion of both degrees in just five years.
Hakia Insight: Students at University at Albany benefit from active collaborations with Leibniz Institute of Photonic Technology and AIM Photonics, connecting classroom learning to the workforce.
Degree Programs
Research Labs & Institutes
Scientific computing and AI workloads
Machine learning and deep learning workloads using NVIDIA DGX systems
Location Advantages
- •Proximity to Albany-based financial services and insurance companies
- •Access to New York State government research and data initiatives
- •Regional tech ecosystem connections in the Northeast
Industry Partners
Career Outcomes
Certifications & Designations
Admissions
Massachusetts Institute of Technology
MIT pioneered many foundational concepts in artificial intelligence and machine learning, housing CSAIL - one of the world's largest and most influential AI research laboratories - where faculty and students work alongside the creators of fundamental algorithms that power modern ML systems.
Massachusetts Institute of Technology Machine Learning Program Overview
Hakia ranks Massachusetts Institute of Technology as the #9 in machine learning degree program.
MIT doesn't offer a traditional standalone master's degree specifically titled "Machine Learning," but provides several pathways for advanced ML education through its world-renowned Computer Science and Artificial Intelligence Laboratory (CSAIL), the Institute for Data, Systems, and Society (IDSS), and the Laboratory for Information and Decision Systems (LIDS). Students can pursue ML through the SM (Scientiae Magister) degree programs in departments like Electrical Engineering and Computer Science, or through specialized programs like the Master of Business Analytics (MBAn) at MIT Sloan, which heavily incorporates machine learning techniques. The Institute also offers a comprehensive Professional Certificate Program in Machine Learning & Artificial Intelligence, requiring 16+ days of qualifying courses taught by leading MIT faculty from CSAIL, IDSS, and LIDS.
MIT's approach to ML education is deeply interdisciplinary, combining rigorous mathematical foundations with cutting-edge research applications. Faculty like Regina Barzilay (natural language processing), Tommi Jaakkola (machine learning theory), and Stefanie Jegelka (graph neural networks) lead breakthrough research while teaching students. The programs emphasize both theoretical understanding and practical implementation, with students often working on real-world problems in healthcare, robotics, climate science, and other domains where MIT's research groups are making significant contributions.
Hakia Insight: Massachusetts Institute of Technology graduates earn $150,000, driven by the program's industry connections and hands-on machine learning curriculum.
Degree Programs
Research Labs & Institutes
Largest AI research lab at MIT, covering ML theory, computer vision, NLP, robotics
Data science and machine learning applications to societal challenges
Mathematical foundations of ML, optimization, and decision-making systems
Location Advantages
- •Kendall Square biotech and startup ecosystem
- •Proximity to Harvard and other Cambridge research institutions
- •Direct access to world's largest concentration of AI-focused companies and venture capital
Industry Partners
Career Outcomes
Certifications & Designations
Admissions
New York University
NYU houses Yann LeCun's legendary CILVR lab and created the world's first 'AI degree' through its MS in Emerging Technologies program, where every student must demonstrate AI fluency regardless of their chosen specialization.
New York University Machine Learning Program Overview
Hakia ranks New York University as the #10 in machine learning degree program.
NYU's machine learning ecosystem spans multiple programs across the Tandon School of Engineering, creating one of the most comprehensive AI education platforms in the country. The traditional MS in Computer Science offers extensive machine learning specialization options, while the innovative MS in Emerging Technologies serves as what NYU calls an 'AI degree for today's world,' allowing students to customize their curriculum across cutting-edge fields with mandatory AI fluency components. Both programs benefit from NYU's powerhouse AI research infrastructure, including the renowned CILVR lab (Computational Intelligence, Learning, Vision, and Robotics) led by Yann LeCun, the Turing Award winner who pioneered convolutional neural networks and serves as Meta's Chief AI Scientist. Students can choose between traditional on-campus experiences in Brooklyn's vibrant tech corridor or fully online formats that maintain the same rigorous curriculum standards.
What sets NYU apart is its unique blend of theoretical depth and practical application, with students working alongside faculty who are literally writing the future of AI. The Emerging Technologies program represents a particularly innovative approach, requiring 6 credits of applied AI courses as core curriculum while allowing students to explore nine different concentration areas from cybersecurity to robotics. Meanwhile, the Computer Science MS provides the foundational rigor that has made NYU a breeding ground for AI leaders, with graduates securing roles at top tech companies and contributing to breakthrough research in machine learning, computer vision, and natural language processing.
Hakia Insight: New York University's Machine Learning for Language (ML²) Group and Algorithms and Foundations Group position students at the forefront of machine learning research.
Degree Programs
Research Labs & Institutes
AI, machine learning, computer perception, natural language understanding, robotics, and healthcare applications
State-of-the-art machine learning methods for natural language processing with emphasis on neural network models
Mathematical and theoretical tools applied to machine learning, systems, and computational biology
Statistics tools, algorithms, and theory for data science and machine learning applications
Career Outcomes
Admissions
Best Machine Learning Programs - Top 10 Online — Complete Program Data
#1. University of Washington-Seattle Campus Machine Learning Program
Hakia ranks University of Washington-Seattle Campus as the #1 in machine learning degree program. Location: Seattle, WA | Type: Public | Tuition: $11,524/year | Graduation Rate: 97% | Score: 97.5
What makes University of Washington-Seattle Campus stand out: UW's engineering-focused AI/ML program is uniquely designed as a stackable degree system where working engineers can earn certificates that build toward a master's, with Boeing Company funding support and specializations spanning everything from robotics to materials science.
Hakia Insight: University of Washington-Seattle Campus graduates earn $165,000, driven by the program's industry connections and hands-on machine learning curriculum.
Program Overview: The University of Washington-Seattle Campus offers two distinct machine learning pathways: the Master of Science in Artificial Intelligence and Machine Learning for Engineering and the Master of Science in Data Science. The AI/ML for Engineering program is a flexible, stackable degree launching Fall 2026 that's specifically designed for working engineers who want to apply AI and ML to physical systems like manufacturing, robotics, and chemical processes. Built with Boeing Company funding support, this program can be completed fully online part-time or as a full-time student, combining foundational AI/ML skills with domain-specific training across multiple engineering disciplines. The complementary MSDS program has been operating since earlier and focuses on professional data science careers, meeting evenings on campus with an industry-relevant curriculum covering statistical modeling, data visualization, and software engineering. Both programs leverage UW's position as a top-10 global university with deep Seattle tech industry connections.
Degree Programs: BS in Computer Science (AI/Machine Learning track) (4 years); MS in Machine Learning (2 years); MS in Computer Science (AI track) (2 years); PhD in Computer Science (AI/ML) (5-6 years)
Research Labs: AI Institute for Dynamic Systems - Real-time learning and control of complex dynamic systems; AI Center for Dynamics & Control - Data-driven discovery and control of dynamical systems; eScience Institute - Data-intensive discovery across all fields using large, complex datasets; SMARTS Lab - Scale-independent Multimodal Automated Real Time Systems
Industry Partners: Boeing Company, Amazon, JP Morgan Chase & Co., Costco IT, Zillow
Career Outcomes:
Notable Faculty: Ali Farhadi (Computer vision, visual understanding, AI for good); Noah Smith (Natural language processing, computational linguistics)
Admissions: GPA: 3.0 minimum cumulative GPA required
Accreditations: ABET accredited
#2. Carnegie Mellon University Machine Learning Program
Hakia ranks Carnegie Mellon University as the #2 in machine learning degree program. Location: Pittsburgh, PA | Type: Private | Tuition: $62,260/year | Graduation Rate: 98% | Score: 85.0
What makes Carnegie Mellon University stand out: CMU houses the world's first academic machine learning department, founded in 2006, and has maintained the #1 ranking in artificial intelligence since 1997 according to U.S. News & World Report.
Hakia Insight: Carnegie Mellon University leverages partnerships with Amazon and Bosch Group to offer students real-world project experience valued by employers.
Program Overview: Carnegie Mellon's Master's in Machine Learning program emerges from the world's first academic machine learning department, founded in 2006. This intensive 16-month program can be completed in three semesters by motivated students, though many take four semesters to deepen their research experience or strengthen foundational skills. The curriculum demands six rigorous core courses spanning probabilistic graphical models to optimization theory, three specialized electives, and a full-time summer practicum that often leads to coveted industry positions. Students work alongside faculty who literally wrote the textbooks on machine learning, with access to cutting-edge research labs studying everything from deep reinforcement learning to AI ethics. The program welcomes students from diverse academic backgrounds - computer science majors study alongside physics PhDs and mathematics graduates - united by exceptional analytical skills and programming proficiency.
Degree Programs: MS (16 months (3-4 semesters)); PhD; Fifth-Year MS; Joint PhD in Statistics and Machine Learning; Joint PhD in Machine Learning and Public Policy; Joint PhD in Neural Computation and Machine Learning
Research Labs: Machine Learning Department - World's first academic ML department with research spanning theoretical foundations to real-world applications
Industry Partners: Amazon, Bosch Group
Career Outcomes:
Notable Faculty: Zico Kolter (Department Head, AI and machine learning)
Admissions: GPA: 3.9/4.0 average for admitted students
Accreditations: STEM
#3. Syracuse University Machine Learning Program
Hakia ranks Syracuse University as the #3 in machine learning degree program. Location: Syracuse, NY | Type: Private | Tuition: $61,310/year | Graduation Rate: 99% | Score: 84.3
What makes Syracuse University stand out: Syracuse University's iSchool has been pioneering information science education since 1928 and uniquely integrates human-centered design principles into AI education, ensuring graduates develop both cutting-edge technical skills and ethical frameworks for responsible AI deployment.
Hakia Insight: Syracuse University's industry network — including NetApp and ADP — provides students with internship and hiring pathways.
Program Overview: Syracuse University's machine learning and AI programs are housed within the innovative School of Information Studies (iSchool), which offers a distinctive interdisciplinary approach combining technology with human-centered design. The flagship Master of Science in Applied Human-Centered Artificial Intelligence is a 31-credit, on-campus program that can be completed in as little as one year, emphasizing hands-on projects and portfolio development. The program stands out for its focus on responsible AI development, featuring core courses in Natural Language Processing, Deep Learning in Practice, and Responsible AI. Students work in state-of-the-art facilities while engaging with faculty like Professor Wanliang Shan, who leads research in soft robotics and machine learning applications. The iSchool also offers a complementary MS in Applied Data Science (34 credits) with specialized tracks in AI, Big Data, and Visual Analytics, available both on-campus and online through their established distance learning platform.
Degree Programs: MS in Applied Human-Centered Artificial Intelligence (1 year minimum); MS in Applied Data Science (Variable); MS in Sport Analytics (Variable)
Research Labs: Shan Research Group (SRG) - Smart, Hybrid, Active and Nature-inspired Materials, Mechanics, and Machines with machine learning applications; BioInspired Institute - Interdisciplinary research including AI applications in biomedical engineering
Industry Partners: NetApp, ADP, PayPal, Uber
Career Outcomes:
Admissions: GPA: 3.0 minimum for Applied Data Science program
Accreditations: ABET
#4. University of California-Irvine Machine Learning Program
Hakia ranks University of California-Irvine as the #4 in machine learning degree program. Location: Irvine, CA | Type: Public | Tuition: $11,834/year | Graduation Rate: 96% | Score: 75.3
What makes University of California-Irvine stand out: Home to the world-famous UCI Machine Learning Repository with 688 datasets used by millions of researchers globally, plus the unique HPI Research Center partnership with Germany's leading tech institute launched in 2020.
Hakia Insight: University of California-Irvine's HPI Research Center in Machine Learning and Data Science creates a direct research-to-career pipeline with Various industry partners, bridging academic research and industry practice.
Program Overview: UC Irvine's machine learning programs span multiple pathways through the Donald Bren School of Information and Computer Sciences, one of only five computing-focused schools among Association of American Universities (AAU) members. The flagship MS in Computer Science offers deep specialization in artificial intelligence and machine learning through its comprehensive core curriculum, with students choosing from seven specialized areas including the dedicated Artificial Intelligence track featuring courses like COMPSCI 273A Machine Learning. For professionals seeking applied expertise, the Master of Data Science (MDS) program provides both full-time and part-time options with industry-focused curriculum emphasizing experiential learning in statistical modeling, machine learning, data management, and AI. The school maintains over 688 datasets in the renowned UCI Machine Learning Repository, serving millions of researchers worldwide and providing students unique access to cutting-edge data resources. With approximately 4,000 undergraduates, 600 master's students, and 400 doctoral students, the school creates an exceptional research environment supported by over 50 Computer Science faculty including 15 ACM Fellows, 13 IEEE Fellows, and 15 AAAS Fellows. Students benefit from the Center for Machine Learning and Intelligent Systems connecting more than thirty faculty across disciplines, plus specialized research centers like the Computational Vision Lab and the HPI Research Center in Machine Learning and Data Science established in 2020. The programs emphasize real-world application through industry capstone projects, with MDS students working directly on data science problems with corporate partners.
Degree Programs: BS (4 years); MS; PhD
Research Labs: Center for Machine Learning and Intelligent Systems - Addresses challenges of the modern data-driven world, using computer algorithms to discover useful information from vast data archives; HPI Research Center in Machine Learning and Data Science - Partnership with Hasso Plattner Institute promoting research and educational activities in ML and data science; Computational Vision Lab - Understanding information processing capabilities of biological visual systems and developing computational systems for visual media; UCI Machine Learning Repository - Maintains 688 datasets as a service to the machine learning community worldwide
Industry Partners: Various industry partners
Career Outcomes: | Top Employers: internet companies, finance, engineering, business, medicine | Common Roles: data scientist, data analyst, statistician
Admissions:
#5. University of Southern California Machine Learning Program
Hakia ranks University of Southern California as the #5 in machine learning degree program. Location: Los Angeles, CA | Type: Private | Tuition: $66,640/year | Graduation Rate: 92% | Score: 75.1
What makes University of Southern California stand out: USC houses the MS in Computer Science - Artificial Intelligence, the first dedicated AI master's program in the United States, while its interdisciplinary approach uniquely combines machine learning with wireless communications, social impact applications, and entertainment industry connections in the heart of Los Angeles.
Hakia Insight: Students at University of Southern California benefit from active collaborations with Amazon and Meta, connecting classroom learning to the workforce.
Program Overview: USC's Viterbi School of Engineering offers a comprehensive suite of machine learning and data science programs that bridge theoretical foundations with real-world applications. The flagship MS in Electrical and Computer Engineering - Machine Learning and Data Science provides focused, rigorous training in data science techniques, machine learning, and signal processing within the wireless communications domain. Complementing this is the MS in Computer Science - Artificial Intelligence, one of the nation's first dedicated AI master's programs, offering specialized tracks in deep learning, computer vision, natural language processing, and robotics. For students seeking broader data science foundations, the MS in Applied Data Science trains professionals from diverse backgrounds through hands-on experiences and a unique professional practicum, emphasizing practical skills in Python programming, database management, and big data infrastructure. All programs require 32 units and can be completed in 1.5-2 years full-time. USC's machine learning ecosystem spans multiple research centers including the USC Center for Artificial Intelligence in Society, the Robotics and Autonomous Systems Center, and specialized labs like the Machine Learning and Data Mining Lab (Melady) and the Computational Social Science Laboratory. Students benefit from LA's tech corridor proximity and USC's extensive alumni network, with graduates placing at top-tier companies like Amazon, Google, Meta, and emerging AI startups.
Degree Programs: MS in Electrical and Computer Engineering - Machine Learning and Data Science (1.5-2 years); MS in Computer Science - Artificial Intelligence (1.5-2 years); MS in Applied Data Science (1.5-2 years)
Research Labs: USC Center for Artificial Intelligence in Society - AI applications for social good including combating human trafficking and wildlife conservation; Machine Learning and Data Mining Lab (Melady) - Advanced machine learning algorithms and data mining techniques; Robotics and Autonomous Systems Center (RASC) - Human-robot interaction, socially assistive robotics, and multi-robot systems; Computational Social Science Laboratory - Data science applications in social sciences and network analysis; Wireless Devices and Systems (WiDeS) Lab - Machine learning applications in wireless communications
Industry Partners: Amazon, Meta, Capital One, Boeing, Intel, Google, Apple, Microsoft, Uber, Qualcomm
Career Outcomes: | Top Employers: Amazon, Google, Microsoft, Apple, Intel, Boeing, Uber, TikTok, Qualcomm | Common Roles: Software Engineer, Machine Learning Engineer, Data Scientist, Computer Vision Engineer, AI Scientist, Product Development Engineer
Admissions:
#6. Indiana University-Bloomington Machine Learning Program
Hakia ranks Indiana University-Bloomington as the #6 in machine learning degree program. Location: Bloomington, IN | Type: Public | Tuition: $10,312/year | Graduation Rate: 84% | Score: 74.0
What makes Indiana University-Bloomington stand out: IU's machine learning programs operate from the $35 million Luddy AI Center within the unique Mind, Brain, and Machine Quad, fostering unprecedented collaboration between AI researchers and cognitive scientists, psychologists, and neuroscientists.
Hakia Insight: Indiana University-Bloomington's industry network — including IBM and Amazon — provides students with internship and hiring pathways.
Program Overview: Indiana University-Bloomington offers machine learning education through multiple pathways within the Luddy School of Informatics, Computing, and Engineering. The flagship program is the PhD in Intelligent Systems Engineering, which advances engineering using artificial intelligence, embedded computing, and sophisticated data interpretation. Students can also pursue machine learning through the MS in Computer Science, which explores AI, machine learning, and big data applications, or the comprehensive Data Science programs that include foundational machine learning coursework across five specialized tracks. The university's $35 million Luddy Artificial Intelligence Center, opened in 2021, serves as the hub for AI and machine learning research, bringing together over 60 faculty members from across the university in the Mind, Brain, and Machine Quad. What sets IU apart is its interdisciplinary approach - the Luddy AI Center connects faculty from nearly every college, creating unique collaboration opportunities between computer science, psychology, cognitive science, and neuroscience. Students gain hands-on experience through practical projects and research early in their studies, with access to advanced cyberinfrastructure including Big Red 200, one of the fastest university-owned supercomputers in the country.
Degree Programs: PhD in Intelligent Systems Engineering (4-6 years); MS in Intelligent Systems Engineering (1.5-2 years); MS in Computer Science (1.5-2 years); BS in Data Science (4 years)
Research Labs: Luddy Artificial Intelligence Center - Human-centered AI research spanning theoretical foundations to societal applications; Vehicle Autonomy and Intelligence Lab - Robot systems for navigation in difficult environments and emergency response; Natural Language Processing Lab - Personalized speech enhancement and recognition systems; Observatory on Social Media - Machine learning for detecting bias and hate speech on social platforms
Industry Partners: IBM, Amazon, Yahoo!
Career Outcomes:
Notable Faculty: David Crandall (Computer vision, machine learning for image and video understanding); Filippo Menczer (Web science, information filtering, and network analysis)
Admissions:
Accreditations: STEM eligible via the U.S. Department of Education
#7. University of Pennsylvania Machine Learning Program
Hakia ranks University of Pennsylvania as the #7 in machine learning degree program. Location: Philadelphia, PA | Type: Private | Tuition: $58,620/year | Graduation Rate: 100% | Score: 73.7
What makes University of Pennsylvania stand out: Penn's MSE-AI is taught by some of the top AI researchers in the world and uniquely emphasizes ethical AI training alongside technical rigor, preparing graduates not just to build AI tools but to responsibly shape the future of this transformative technology.
Hakia Insight: University of Pennsylvania's industry network — including AWS and Google — provides students with internship and hiring pathways.
Program Overview: Penn Engineering's Master of Science in Engineering in Artificial Intelligence (MSE-AI Online) is a fully online, asynchronous program that equips students with both cutting-edge technical skills and robust ethical frameworks for AI development. Known as The Raj and Neera Singh Program in Artificial Intelligence, this degree covers classical AI, natural language processing, generative AI, and modern deep learning while preparing students to address AI's societal risks head-on. The program is designed for professionals with computer science or engineering backgrounds who want to stay ahead of industry demand while studying from anywhere in the world. Students benefit from Penn's world-renowned AI faculty and engage with real-world tools and environments through hands-on assignments, all while being part of a tight-knit online community supported by robust engagement platforms.
Degree Programs: BSE (4 years); MSE (1.5-2 years)
Research Labs: GRASP Lab (General Robotics, Automation, Sensing & Perception) - Premier research center in robotics, vision, perception, control, and learning; ASSET Center - AI-Enabled Systems: Safe, Explainable and Trustworthy; The Warren Center for Network & Data Sciences - Network science, economics, sociology, and cryptography approaches to data; IDEAS Center - Innovation in Data Engineering and Science
Industry Partners: AWS, Google
Career Outcomes: | Common Roles: Startup founders, AI model builders, AI integration specialists
Notable Faculty: Chris Callison-Burch (Program Director, MSE-AI Online)
Admissions:
#8. University at Albany Machine Learning Program
Hakia ranks University at Albany as the #8 in machine learning degree program. Location: Albany, NY | Type: Public | Tuition: $7,070/year | Graduation Rate: 99% | Score: 72.8
What makes University at Albany stand out: UAlbany is one of the few universities to integrate topological data analysis as a core component of its data science curriculum, offering specialized training in this emerging field alongside traditional machine learning and statistics.
Hakia Insight: Students at University at Albany benefit from active collaborations with Leibniz Institute of Photonic Technology and AIM Photonics, connecting classroom learning to the workforce.
Program Overview: The University at Albany offers a Master of Science in Data Science that uniquely positions itself at the intersection of mathematics, machine learning, and cutting-edge topological data analysis. Housed in the Department of Mathematics within the College of Arts and Sciences, this program provides comprehensive training across three core areas: topological data analysis, machine learning, and statistics. Students gain hands-on experience with current industry tools including Python, R, TensorFlow, and specialized topological data analysis software like Ayasdi's Mapper, Eirene, and Ripser. The program features a flexible curriculum structure with core requirements, specialized tracks, and practical components including comprehensive data analysis projects with oral presentations. Students can tailor their learning path through electives and practicum courses in either topological data analysis or machine learning. The program is designated as STEM, offering international students extended Optional Practical Training opportunities of up to 36 months. UAlbany also offers a unique 4+1 accelerated option for current undergraduates, allowing completion of both degrees in just five years.
Degree Programs: BS in Computer Science (ML concentration) (4 years); MS in Computer Science (2 years)
Research Labs: High Performance Computing Center - Scientific computing and AI workloads; AI Supercomputer Lab - Machine learning and deep learning workloads using NVIDIA DGX systems
Industry Partners: Leibniz Institute of Photonic Technology, AIM Photonics
Career Outcomes:
Admissions: GPA: 3.0 minimum for accelerated option | Acceptance Rate: Rolling admissions
Accreditations: AACSB Accredited, STEM
#9. Massachusetts Institute of Technology Machine Learning Program
Hakia ranks Massachusetts Institute of Technology as the #9 in machine learning degree program. Location: Cambridge, MA | Type: Private | Tuition: $59,750/year | Score: 70.6
What makes Massachusetts Institute of Technology stand out: MIT pioneered many foundational concepts in artificial intelligence and machine learning, housing CSAIL - one of the world's largest and most influential AI research laboratories - where faculty and students work alongside the creators of fundamental algorithms that power modern ML systems.
Hakia Insight: Massachusetts Institute of Technology graduates earn $150,000, driven by the program's industry connections and hands-on machine learning curriculum.
Program Overview: MIT doesn't offer a traditional standalone master's degree specifically titled "Machine Learning," but provides several pathways for advanced ML education through its world-renowned Computer Science and Artificial Intelligence Laboratory (CSAIL), the Institute for Data, Systems, and Society (IDSS), and the Laboratory for Information and Decision Systems (LIDS). Students can pursue ML through the SM (Scientiae Magister) degree programs in departments like Electrical Engineering and Computer Science, or through specialized programs like the Master of Business Analytics (MBAn) at MIT Sloan, which heavily incorporates machine learning techniques. The Institute also offers a comprehensive Professional Certificate Program in Machine Learning & Artificial Intelligence, requiring 16+ days of qualifying courses taught by leading MIT faculty from CSAIL, IDSS, and LIDS. MIT's approach to ML education is deeply interdisciplinary, combining rigorous mathematical foundations with cutting-edge research applications. Faculty like Regina Barzilay (natural language processing), Tommi Jaakkola (machine learning theory), and Stefanie Jegelka (graph neural networks) lead breakthrough research while teaching students. The programs emphasize both theoretical understanding and practical implementation, with students often working on real-world problems in healthcare, robotics, climate science, and other domains where MIT's research groups are making significant contributions.
Degree Programs: SM in Electrical Engineering and Computer Science (1-2 years); Master of Business Analytics (MBAn) (1 year); Professional Certificate in ML & AI (Varies (36 months max))
Research Labs: Computer Science and Artificial Intelligence Laboratory (CSAIL) - Largest AI research lab at MIT, covering ML theory, computer vision, NLP, robotics; Institute for Data, Systems, and Society (IDSS) - Data science and machine learning applications to societal challenges; Laboratory for Information and Decision Systems (LIDS) - Mathematical foundations of ML, optimization, and decision-making systems
Industry Partners: Google, Microsoft, Amazon, OpenAI, IBM, DeepMind
Career Outcomes: Placement Rate: 95%+
Notable Faculty: Dario Amodei (Deep learning and AI safety); Regina Barzilay (Machine learning for drug discovery and chemistry); Tomaso Poggio (Computational neuroscience and deep learning theory); Stefanie Mueller (Human-computer interaction and machine learning applications)
Admissions:
Accreditations: ABET accredited
#10. New York University Machine Learning Program
Hakia ranks New York University as the #10 in machine learning degree program. Location: New York, NY | Type: Private | Tuition: $60,438/year | Score: 70.5
What makes New York University stand out: NYU houses Yann LeCun's legendary CILVR lab and created the world's first 'AI degree' through its MS in Emerging Technologies program, where every student must demonstrate AI fluency regardless of their chosen specialization.
Hakia Insight: New York University's Machine Learning for Language (ML²) Group and Algorithms and Foundations Group position students at the forefront of machine learning research.
Program Overview: NYU's machine learning ecosystem spans multiple programs across the Tandon School of Engineering, creating one of the most comprehensive AI education platforms in the country. The traditional MS in Computer Science offers extensive machine learning specialization options, while the innovative MS in Emerging Technologies serves as what NYU calls an 'AI degree for today's world,' allowing students to customize their curriculum across cutting-edge fields with mandatory AI fluency components. Both programs benefit from NYU's powerhouse AI research infrastructure, including the renowned CILVR lab (Computational Intelligence, Learning, Vision, and Robotics) led by Yann LeCun, the Turing Award winner who pioneered convolutional neural networks and serves as Meta's Chief AI Scientist. Students can choose between traditional on-campus experiences in Brooklyn's vibrant tech corridor or fully online formats that maintain the same rigorous curriculum standards. What sets NYU apart is its unique blend of theoretical depth and practical application, with students working alongside faculty who are literally writing the future of AI. The Emerging Technologies program represents a particularly innovative approach, requiring 6 credits of applied AI courses as core curriculum while allowing students to explore nine different concentration areas from cybersecurity to robotics. Meanwhile, the Computer Science MS provides the foundational rigor that has made NYU a breeding ground for AI leaders, with graduates securing roles at top tech companies and contributing to breakthrough research in machine learning, computer vision, and natural language processing.
Degree Programs: MS in Computer Science with Machine Learning & AI Concentration (2 years); MS in Emerging Technologies with Machine Learning & AI Concentration (2 years)
Research Labs: CILVR (Computational Intelligence, Learning, Vision, and Robotics) - AI, machine learning, computer perception, natural language understanding, robotics, and healthcare applications; Machine Learning for Language (ML²) Group - State-of-the-art machine learning methods for natural language processing with emphasis on neural network models; Algorithms and Foundations Group - Mathematical and theoretical tools applied to machine learning, systems, and computational biology; STAT Research Group - Statistics tools, algorithms, and theory for data science and machine learning applications
Career Outcomes: | Common Roles: applications programming, big data, software engineering, machine learning and AI, computer vision and imaging, interactive data visualization
Notable Faculty: Brandon Reagen (deep learning and privacy preserving computation); Yi-Jen Chiang (Computer Science, MS Program Director); Edward Wong (Computer Science, Program Admissions Chair)
Admissions:
Best Machine Learning Programs - Compare Top 5 Online
| School | Location | Type | Tuition | Grad Rate | Score |
|---|---|---|---|---|---|
| #1 University of Washington-Seattle Campus | Seattle, WA | Public | $11,524 | 97% | 97.5/100 |
| #2 Carnegie Mellon University | Pittsburgh, PA | Private | $62,260 | 98% | 85/100 |
| #3 Syracuse University | Syracuse, NY | Private | $61,310 | 99% | 84.3/100 |
| #4 University of California-Irvine | Irvine, CA | Public | $11,834 | 96% | 75.3/100 |
| #5 University of Southern California | Los Angeles, CA | Private | $66,640 | 92% | 75.1/100 |
Top 25 Online Machine Learning Degree Programs 2026
| Rank | |||||||
|---|---|---|---|---|---|---|---|
| 1 | University of Washington-Seattle Campus | Seattle, WA | Public | $11,524 | 97% | — | 97.5 |
| 2 | Carnegie Mellon University | Pittsburgh, PA | Private | $62,260 | 98% | — | 85 |
| 3 | Syracuse University | Syracuse, NY | Private | $61,310 | 99% | — | 84.3 |
| 4 | University of California-Irvine | Irvine, CA | Public | $11,834 | 96% | — | 75.3 |
| 5 | University of Southern California | Los Angeles, CA | Private | $66,640 | 92% | — | 75.1 |
| 6 | Indiana University-Bloomington | Bloomington, IN | Public | $10,312 | 84% | — | 74 |
| 7 | University of Pennsylvania | Philadelphia, PA | Private | $58,620 | 100% | — | 73.7 |
| 8 | University at Albany | Albany, NY | Public | $7,070 | 99% | — | 72.8 |
| 9 | Massachusetts Institute of Technology | Cambridge, MA | Private | $59,750 | — | — | 70.6 |
| 10 | New York University | New York, NY | Private | $60,438 | — | — | 70.5 |
| 11 | University of Michigan-Ann Arbor | Ann Arbor, MI | Public | $17,977 | 92% | — | 68.6 |
| 12 | Northwestern University | Evanston, IL | Private | $64,887 | 90% | — | 67.5 |
| 13 | Clark University | Worcester, MA | Private | $54,760 | 98% | — | 66.2 |
| 14 | Northeastern University | Boston, MA | Private | $62,000 | — | — | 65.4 |
| 15 | Brandeis University | Waltham, MA | Private | $64,348 | 99% | — | 65.4 |
| 16 | University of San Diego | San Diego, CA | Private | $55,690 | 97% | — | 65.1 |
| 17 | University of Massachusetts-Amherst | Amherst, MA | Public | $16,591 | 90% | — | 64.1 |
| 18 | Emory University | Atlanta, GA | Private | $59,920 | 97% | — | 63.2 |
| 19 | San Jose State University | San Jose, CA | Public | $5,742 | 100% | — | 63.1 |
| 20 | Rochester Institute of Technology | Rochester, NY | Private | $55,784 | 90% | — | 62.7 |
| 21 | The University of Texas at Austin | Austin, TX | Public | $11,678 | 89% | — | 62.4 |
| 22 | University of California-Santa Cruz | Santa Cruz, CA | Public | $11,834 | 93% | — | 62.3 |
| 23 | University of Central Florida | Orlando, FL | Public | $4,478 | 93% | — | 61.4 |
| 24 | University of Georgia | Athens, GA | Public | $9,790 | 95% | — | 60.9 |
| 25 | University of Pittsburgh-Pittsburgh Campus | Pittsburgh, PA | Public | $20,154 | 88% | — | 60.6 |
Showing 1–25 of 50
Online Machine Learning Degree Programs Overview
Online machine learning degree programs provide flexible pathways to enter the rapidly growing AI/ML engineering field. These programs combine rigorous computer science fundamentals with specialized coursework in artificial intelligence and data science methodologies. According to IPEDS 2023 data, 156 accredited institutions now offer fully online machine learning or AI-focused degree programs, representing a 340% increase from 2018.
The best online programs maintain the same academic rigor as their on-campus counterparts while offering asynchronous learning, industry partnerships, and direct access to cutting-edge research. Students can pursue data science degrees with ML specializations, computer science master's with AI tracks, or dedicated machine learning programs. Graduates typically enter roles as data scientists, AI engineers, research scientists, or software engineers specializing in machine learning systems.
Our ranking methodology analyzes graduation rates, career outcomes, faculty credentials, industry partnerships, and student satisfaction across 156 programs. We prioritize programs that offer hands-on projects, real-world datasets, and strong placement rates in top-tier technology companies. Many programs also provide pathways to valuable AI/ML certifications and preparation for technical interviews at major tech firms.
Online Learning Formats Explained
Online Machine Learning programs offer multiple learning formats to accommodate different schedules and learning preferences. Understanding these formats helps you choose a program that fits your lifestyle.
Synchronous (Live) Learning:
- Real-time video lectures at scheduled times (often evenings/weekends)
- Live interaction with professors and classmates
- Immediate Q&A and discussion; feels most like traditional classroom
- Requires reliable internet and schedule commitment
Asynchronous (Self-Paced) Learning:
- Pre-recorded lectures watched on your schedule
- Weekly deadlines but flexible daily timing
- Discussion forums replace live interaction
- Ideal for working professionals with irregular schedules
Hybrid/Blended Programs:
- Combines online coursework with periodic in-person sessions
- Typically 1-2 weekend residencies per semester
- Best of both worlds: flexibility plus networking opportunities
- Often required for programs with lab components
How to Verify Accreditation
Accreditation verification is critical when choosing an online Machine Learning program. Degrees from unaccredited institutions may not be recognized by employers or other universities. According to the Council for Higher Education Accreditation, only properly accredited degrees qualify for federal financial aid and professional licensure.
How to Verify Accreditation:
- Check regional accreditation — Look up the institution at CHEA Database or Department of Education Database
- Verify ABET accreditation — For engineering/CS programs, ABET accreditation signals program quality
- Confirm identical credential — Online degrees should state the same institution as on-campus degrees (e.g., "Arizona State University" not "ASU Online")
- Check employer recognition — Review job postings in your target field for degree requirements
Red Flags to Avoid:
- Accreditation from agencies not recognized by CHEA or DOE
- "Accredited" only by an agency the school itself created
- Degrees offered in weeks rather than months/years
- No faculty credentials listed; "life experience" credits
Do Employers Respect Online Degrees?
Employer perception of online Machine Learning degrees has shifted dramatically. According to a SHRM survey, 83% of HR managers now view online degrees from accredited institutions as equivalent to traditional degrees—up from 50% a decade ago.
What Employers Actually Care About:
- Institution reputation matters more than delivery format; a Georgia Tech online degree carries the same weight as on-campus
- Skills demonstration — Portfolio projects, GitHub contributions, and certifications often outweigh degree format
- Major tech companies (Google, Apple, Meta) have removed degree requirements entirely for many roles
- Consistency — Degree should list the institution name, not "Online Division" or similar
The COVID Shift: The pandemic normalized remote work and online education. Gallup research shows that 72% of executives who managed remote teams reported equal or higher productivity, reducing stigma around online credentials.
Best Practice: Don't mention "online" on your resume—simply list the degree and institution. If asked in interviews, emphasize the rigor and self-discipline required for online study.
Technology Requirements
Online Machine Learning programs require specific technology to participate effectively. Meeting these requirements before enrollment prevents frustrating technical issues during coursework.
Minimum Hardware Requirements:
- Computer — Windows 10/11 or macOS 10.15+; 8GB RAM minimum (16GB recommended for development work)
- Processor — Intel i5/AMD Ryzen 5 or better; critical for compiling code and running VMs
- Storage — 256GB SSD minimum; software development requires significant disk space
- Webcam/Microphone — Required for proctored exams and group projects
- Internet — 25 Mbps download minimum; wired connection recommended for exams
Software Typically Provided:
- Free access to development tools (JetBrains IDEs, Visual Studio, etc.) via student licenses
- Cloud computing credits (AWS, Azure, GCP) — typically $100-$500 per course
- Virtual lab environments for networking, security, or systems courses
- Collaboration tools (Slack, Microsoft Teams, Zoom) included with enrollment
Proctored Exams: What to Expect
Most online Machine Learning programs use proctored exams to ensure academic integrity. Understanding what to expect reduces test anxiety and technical issues.
Common Proctoring Methods:
- AI-proctored (ProctorU, Examity) — Software monitors via webcam; flags suspicious behavior for human review
- Live proctored — Real person watches via video throughout the exam
- Lockdown browser — Prevents accessing other applications; may combine with AI monitoring
- In-person testing centers — Some programs offer or require local testing site options
Preparing for Proctored Exams:
- Test your setup early — Run system checks 24-48 hours before; most services offer practice sessions
- Prepare your environment — Clean desk, good lighting, no one else in room, pets secured
- Valid ID required — Government-issued photo ID; check name matches enrollment exactly
- Stable internet — Wired connection preferred; have phone hotspot as backup
- Know the rules — No headphones, no leaving frame, no reading questions aloud (varies by exam)
Career Paths
Machine Learning Engineer
SOC 15-1299Design and implement ML systems in production environments. Build scalable ML pipelines and deploy models for real-world applications.
Data Scientist
SOC 15-2051Extract insights from complex datasets using statistical analysis and machine learning techniques. Communicate findings to stakeholders and drive business decisions.
AI Research Scientist
SOC 15-1221Conduct advanced research in artificial intelligence and machine learning. Publish papers and develop new algorithms and techniques.
Software Engineer - AI/ML
SOC 15-1252Develop software applications that incorporate machine learning capabilities. Build intelligent systems and AI-powered features.
Computer Vision Engineer
SOC 15-1299Specialize in image and video analysis using deep learning. Develop applications for autonomous vehicles, medical imaging, and robotics.
Natural Language Processing Engineer
SOC 15-1299Build systems that understand and generate human language. Work on chatbots, translation systems, and text analysis tools.
Top States for Online Machine Learning Programs
| State | Total Programs | Median Tuition | Top Program |
|---|---|---|---|
| Best Machine Learning Online Programs in New York | 18 | $45,200 | Columbia University |
| Best Machine Learning Online Programs in Texas | 15 | $22,100 | University of Texas at Austin |
| Best Machine Learning Online Programs in Massachusetts | 12 | $55,000 | MIT |
| Best Machine Learning Online Programs in Illinois | 11 | $25,800 | University of Illinois Urbana-Champaign |
| Best Machine Learning Online Programs in Pennsylvania | 10 | $38,900 | Carnegie Mellon University |
| Best Machine Learning Online Programs in Washington | 8 | $19,500 | University of Washington |
| Best Machine Learning Online Programs in Georgia | 7 | $12,400 | Georgia Institute of Technology |
| Best Machine Learning Online Programs in Maryland | 6 | $24,700 | Johns Hopkins University |
| Best Machine Learning Online Programs in Virginia | 5 | $18,200 | Virginia Tech |
Financial Aid and Funding Options for Online ML Programs
Online machine learning students have access to multiple funding sources including federal aid, employer sponsorship, and program-specific scholarships. According to our survey of 1,200+ online students, 67% receive some form of financial assistance. Many employers offer tuition reimbursement for ML skills development, recognizing the strategic value of upskilling current employees.
Federal financial aid through FAFSA covers online programs at accredited institutions. Graduate students can borrow up to $20,500 annually through federal loans with competitive interest rates. Many programs offer payment plans that allow students to spread costs across multiple terms, making education more accessible for working professionals.
Several organizations provide scholarships for women in technology and underrepresented minorities pursuing ML education. Companies like Google, Microsoft, and Amazon offer sponsored seats in top programs for employees and diversity candidates. Veterans can use GI Bill benefits for many online programs, though students should verify program approval with the VA before enrolling.
Machine Learning & AI Career Track
+$25K avg salary increase·9 months
- University of Arizona graduate certificate included
- 1-on-1 mentorship from industry professionals
- Money-back job guarantee
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Frequently Asked Questions About Online ML Degrees
Data Sources and Methodology
Institutional completion rates, enrollment data, and tuition costs for all accredited programs
Occupational employment and wage statistics for ML-related careers (SOC codes 15-1252, 15-2051, 15-1299)
Direct surveys of program administrators at 156 institutions covering curriculum, partnerships, and graduate outcomes
Analysis of 2,400+ verified reviews from Reddit, LinkedIn, Google Reviews, and Niche.com (Jan 2024 - Dec 2025)
LinkedIn analysis of 15,000+ online ML program graduates for career progression and salary data
Taylor Rupe
Co-founder & Editor (B.S. Computer Science, Oregon State • B.A. Psychology, University of Washington)
Taylor combines technical expertise in computer science with a deep understanding of human behavior and learning. His dual background drives Hakia's mission: leveraging technology to build authoritative educational resources that help people make better decisions about their academic and career paths.