Best Value Machine Learning Degree Programs 2026

Best Machine Learning Programs - Top 10 Best Value, Complete Program Data

1. #1. University of Washington-Seattle Campus — Machine Learning

   Hakia ranks University of Washington-Seattle Campus's machine learning program #1. Delivery: on-campus. Location: Seattle, WA | Type: Public | Tuition: $11,524/year | Graduation Rate: 97% | Score: 95.1

   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. #2. Indiana University-Bloomington — Machine Learning

   Hakia ranks Indiana University-Bloomington's machine learning program #2. Delivery: on-campus. Location: Bloomington, IN | Type: Public | Tuition: $10,312/year | Graduation Rate: 84% | Score: 78.9

   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, building 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

3. #3. University of California-Irvine — Machine Learning

   Hakia ranks University of California-Irvine's machine learning program #3. Delivery: on-campus. Location: Irvine, CA | Type: Public | Tuition: $11,834/year | Graduation Rate: 96% | Score: 78.0

   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 advanced 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:

4. #4. University at Albany — Machine Learning

   Hakia ranks University at Albany's machine learning program #4. Delivery: on-campus. Location: Albany, NY | Type: Public | Tuition: $7,070/year | Graduation Rate: 99% | Score: 75.4

   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 advanced 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

5. #5. University of Southern California — Machine Learning

   Hakia ranks University of Southern California's machine learning program #5. Delivery: on-campus. Location: Los Angeles, CA | Type: Private | Tuition: $66,640/year | Graduation Rate: 92% | Score: 71.7

   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. #6. Carnegie Mellon University — Machine Learning

   Hakia ranks Carnegie Mellon University's machine learning program #6. Delivery: on-campus. Location: Pittsburgh, PA | Type: Private | Tuition: $62,260/year | Graduation Rate: 98% | Score: 68.8

   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 advanced 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

7. #7. University of Massachusetts-Amherst — Machine Learning

   Hakia ranks University of Massachusetts-Amherst's machine learning program #7. Delivery: on-campus. Location: Amherst, MA | Type: Public | Tuition: $16,591/year | Graduation Rate: 90% | Score: 60.7

   What makes University of Massachusetts-Amherst stand out: UMass Amherst's program emphasizes production-scale machine learning systems and large-scale data problems, preparing students for real-world infrastructure challenges.

   Hakia Insight: University of Massachusetts-Amherst's direct partnerships with Google and Microsoft give students a competitive edge through industry-embedded projects and recruiting pipelines.

   Program Overview: UMass Amherst's machine learning program is known for its emphasis on large-scale systems and real-world data challenges, grounded in foundational computer science and statistics. The curriculum progresses from core ML theory through specialized tracks in deep learning, reinforcement learning, and data mining, with significant lab work on datasets and computational problems that mirror industry scale. Faculty research spans autonomous systems, natural language understanding, and machine learning infrastructure, areas where UMass has built particular strength. Students benefit from active industry partnerships that bring practitioners to campus and open internship pipelines to major tech companies. The program balances academic rigor with pragmatism. Coursework includes hands-on experience with distributed systems, cloud computing platforms, and modern ML frameworks. Many graduates transition directly into machine learning engineer roles at tech companies or continue to doctoral research in AI. The Five College Consortium (UMass, Amherst, Hampshire, Mount Holyoke, Smith) expands research and course offerings, while proximity to Boston's innovation ecosystem creates networking and recruiting opportunities.

   Degree Programs: BS in Computer Science (Machine Learning track) (4 years); MS in Computer Science (Machine Learning focus) (2 years); PhD in Computer Science (Machine Learning specialization) (5-6 years)

   Research Labs: College of Information and Computer Sciences - Machine Learning and Intelligent Information Processing Lab - Machine learning, natural language processing, and data mining; Autonomous Learning Laboratory - Reinforcement learning and autonomous systems

   Industry Partners: Google, Microsoft, Amazon, IBM

   Career Outcomes:

   Notable Faculty: Andrew McCallum (Machine learning, natural language processing, and statistical relational learning); Shlomo Zilberstein (Artificial intelligence and decision-making under uncertainty)

   Admissions:

   Accreditations: ABET accredited (BS program)

8. #8. The University of Texas at Austin — Machine Learning

   Hakia ranks The University of Texas at Austin's machine learning program #8. Delivery: on-campus. Location: Austin, TX | Type: Public | Tuition: $11,678/year | Graduation Rate: 89% | Score: 60.1

   What makes The University of Texas at Austin stand out: One of the first AI master's programs available 100% online, featuring asynchronous instructor-paced courses with on-demand lectures designed for working professionals' schedules.

   Hakia Insight: The University of Texas at Austin graduates earn $150,000, driven by the program's industry connections and hands-on machine learning curriculum.

   Program Overview: The University of Texas at Austin offers an online Master's in Artificial Intelligence program, one of the first AI master's programs available 100% online. The program covers reasoning under uncertainty, ethics in AI, machine learning case studies, deep learning, and more, preparing graduates to lead AI innovations across various industries.

   Degree Programs: Master's in Artificial Intelligence

   Career Outcomes: | Top Employers: Uber, Netflix, Amazon | Common Roles: AI Engineer, Machine Learning Engineer, AI Research Scientist, Prompt Engineer, Big Data Engineer, NLP Engineer, Deep Learning Engineer, Business Intelligence Developer, Computer Vision Engineer, AI Consultant

   Notable Faculty: Dr. Philipp Krähenbühl (Deep Learning, Computer Vision); Dr. Ken Fleischmann (Ethics in AI); Dr. Adam Klivans (Machine Learning); Dr. Qiang Liu (Machine Learning, Deep Generative Models); Dr. Joydeep Biswas (Planning, Search, and Reasoning Under Uncertainty); Dr. Peter Stone (Reinforcement Learning); Dr. Scott Niekum (Reinforcement Learning)

   Admissions:

9. #9. University of Michigan-Ann Arbor — Machine Learning

   Hakia ranks University of Michigan-Ann Arbor's machine learning program #9. Delivery: on-campus. Location: Ann Arbor, MI | Type: Public | Tuition: $17,977/year | Graduation Rate: 92% | Score: 59.1

   What makes University of Michigan-Ann Arbor stand out: Elite research-focused program with faculty, advanced labs, and Fortune 500 industry partnerships, preparing students for PhD programs, senior research roles, or top-tier tech companies.

   Hakia Insight: Students at University of Michigan-Ann Arbor benefit from active collaborations with Google and Meta, connecting classroom learning to the workforce.

   Program Overview: Michigan Engineering's machine learning and AI programs rank among the nation's most rigorous, rooted in faculty conducting advanced research across computer vision, natural language processing, robotics, and reinforcement learning. Students gain access to top-tier research labs and can pursue specialized tracks in areas like autonomous systems and human-centered AI alongside their core studies. The university's industrial partnerships with companies like Ford, Google, Amazon, and Meta provide internships, capstone collaborations, and recruitment pipelines. Graduate outcomes reflect the program's prestige: students consistently secure positions at top tech firms, enter prestigious PhD programs, or launch AI startups. Both undergraduate and graduate curricula emphasize mathematical depth, linear algebra, probability, optimization, ensuring students understand not just how to apply ML tools but why they work. The Ann Arbor location, combined with UMich's research computing infrastructure and peer group of highly motivated students, creates an environment where students routinely publish in top-tier venues during their studies.

   Degree Programs: BS in Computer Science (AI/ML focus) (4 years); MS in Computer Science (AI/ML specialization) (2 years); PhD in Computer Science (AI/ML areas) (5-6 years)

   Research Labs: Michigan Artificial Intelligence Lab (AI Lab) - Machine learning, computer vision, natural language processing; Robotics Institute - Autonomous systems, robot learning, human-robot interaction; Software Systems Laboratory - Machine learning systems, optimization

   Industry Partners: Google, Meta, Amazon, Ford, Microsoft

   Career Outcomes: | Top Employers: Google, Meta, Amazon, Microsoft, Apple, DeepMind | Common Roles: Machine Learning Engineer, Research Scientist, Software Engineer (ML), PhD Student at top programs

   Notable Faculty: Honglak Lee (Deep learning, computer vision, reinforcement learning); Raj Pandya (Machine learning systems, optimization)

   Admissions:

   Accreditations: ABET accredited (engineering programs)

10. #10. University of Louisiana at Lafayette — Machine Learning

    Hakia ranks University of Louisiana at Lafayette's machine learning program #10. Delivery: on-campus. Location: Lafayette, LA | Type: Public | Tuition: $5,407/year | Graduation Rate: 98% | Score: 56.5

    What makes University of Louisiana at Lafayette stand out: A regionally-connected, application-focused program that prepares students to deploy machine learning in energy, healthcare, and manufacturing contexts rather than purely research-oriented machine learning.

    Hakia Insight: Proximity to Louisiana's energy sector and offshore technology companies

    Program Overview: UL Lafayette's machine learning pathway emphasizes practical application within a computer science curriculum that bridges theory and industry need. The program integrates machine learning fundamentals through core computer science coursework while offering electives in data mining, artificial intelligence, and advanced algorithms that appeal to students targeting predictive analytics and intelligent systems roles. Faculty maintain active research interests in machine learning applications, creating opportunities for undergraduates and graduate students to engage in real problem-solving beyond the classroom. The university's location in Louisiana's growing tech corridor and partnerships with regional energy, healthcare, and manufacturing sectors provide internship pipelines where students apply machine learning to domain-specific challenges, from reservoir simulation to medical imaging. Graduates move into roles at mid-size tech firms, consulting practices, and industry labs throughout the South, with a meaningful subset pursuing advanced degrees at R1 institutions. The program's strength lies not in advanced specialization but in producing technically capable engineers who can implement machine learning solutions in resource-constrained or domain-heavy environments where theoretical perfection matters less than pragmatic delivery.

    Degree Programs: Bachelors in Machine Learning

    Career Outcomes: | Top Employers: CGI Technologies & Solutions, Perficient, Inc., Enquero

    Admissions:

    Accreditations: ABET