Best Machine Learning Degree Programs

Best Machine Learning Programs - Top 10 — Complete Program Data

1. #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: Students at University of Washington-Seattle Campus benefit from active collaborations with Boeing Company and Amazon, connecting classroom learning to the workforce.

   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: | Top Employers: JP Morgan Chase & Co., Parsons Corporation, IBM, Costco IT, Toyota, Northrop Grumman, Zillow, Seattle Children's Hospital | Common Roles: Software Engineer, Research Scientist, Data Scientist, Consultant

   Notable Faculty: Steve Brunton (Machine learning for dynamical systems, sparse sensing, dimensionality reduction); Ashis Banerjee (Automated decision-making for cyber-physical systems, optimization, machine learning); Taylor Kessler Faulkner (AI, human-robot interaction, assistive robotics)

   Admissions: GPA: 3.0 minimum cumulative GPA required

   Accreditations: ABET accredited

2. #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: 94.4

   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: | Top Employers: Major technology companies, AI startups, Research institutions | Common Roles: Machine Learning Engineer, AI Software Engineer, Research Scientist, Data Scientist

   Notable Faculty: Zico Kolter (Department Head, AI and machine learning)

   Admissions: GPA: 3.9/4.0 average for admitted students

   Accreditations: STEM program designation for international students

3. #3. University of Southern California Machine Learning Program

   Hakia ranks University of Southern California as the #3 in machine learning degree program. Location: Los Angeles, CA | Type: Private | Tuition: $66,640/year | Graduation Rate: 92% | Score: 92.5

   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, Meta, Microsoft, Uber, TikTok, Goldman Sachs, Applied Materials | Common Roles: Software Development Engineer, Machine Learning Engineer, Data Scientist, Applied Scientist, Computer Vision Engineer

   Notable Faculty: Prof. Andreas Molisch (Wireless communications and machine learning integration); Prof. Xiaohui Chen (High-dimensional statistics, machine learning, optimal transport)

   Admissions:

   Accreditations: OPT STEM extension eligible

4. #4. Syracuse University Machine Learning Program

   Hakia ranks Syracuse University as the #4 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: Placement Rate: 96% for iSchool undergraduates (2024), 90% for Applied Data Science masters (2024) | Top Employers: NetApp, ADP, PayPal, SmartestEnergy | Common Roles: Machine Learning Engineer, Data Scientist, Software Engineer, Business Intelligence Developer, Research Scientist, Big Data Architect

   Notable Faculty: Dr. Wanliang Shan (Machine learning applications in soft robotics and materials engineering); Dr. Jaime Banks (Social AI and human-machine interaction research); Dr. Jenny Stromer-Galley (Political communication, social media, and digital behavior analysis); Dr. Michael Fudge (Cloud computing, data science, and human-centered design)

   Admissions: GPA: 3.0 minimum for Applied Data Science program

   Accreditations: Middle States Commission on Higher Education accreditation, American Library Association accreditation (since 1928)

5. #5. University of California-Irvine Machine Learning Program

   Hakia ranks University of California-Irvine as the #5 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: | Common Roles: Data Scientist, Machine Learning Engineer, Research positions

   Notable Faculty: undefined (50+ Computer Science faculty including 15 ACM Fellows, 13 IEEE Fellows, 15 AAAS Fellows, plus AAAI Fellows and Academia Europea Members)

   Admissions:

   Accreditations: Minority Serving Institution (MSI), Hispanic-Serving Institution (HSI), Asian American and Native American Pacific Islander-Serving Institution (AANAPISI)

6. #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: Placement Rate: 100% within 6 months (MS Computer Science 2022) | Top Employers: IBM, Yahoo!, Amazon, Cerner, Expedia | Common Roles: Software Engineer, Technical Consultant, Security Consultant, Data Scientist, Research Scientist

   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. #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: AI Startup Founders, AI Model Developers, AI Integration Specialists

   Notable Faculty: Chris Callison-Burch (Computer and Information Science, Natural Language Processing); George J. Pappas (Electrical and Systems Engineering, Transportation); Rajeev Alur (Computer and Information Science); Michael Kearns (Management & Technology)

   Admissions:

8. #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: | Common Roles: Algorithm developer, Business intelligence analyst, Data scientist, Data architect, Data engineer, Machine learning engineer, Distributed systems engineer

   Notable Faculty: Dr. Igor Lednev (Raman spectroscopy, machine learning for forensic applications and medical diagnostics)

   Admissions: GPA: 3.0 minimum for accelerated option | Acceptance Rate: Rolling admissions

   Accreditations: STEM designation, F-1 STEM OPT extension eligible

9. #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: Regina Barzilay (Natural language processing and healthcare AI); Tommi S. Jaakkola (Machine learning theory and probabilistic models); Stefanie Jegelka (Graph neural networks and optimization); Antonio Torralba (Computer vision and visual AI); Vivienne Sze (Efficient deep learning systems and hardware)

   Admissions:

   Accreditations: ABET accredited

10. #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: | Top Employers: Amazon, Microsoft, Google, Meta, Bloomberg, JPMorgan Chase | Common Roles: AI Engineer, Data Scientist, Machine Learning Engineer, Research Engineer, Software Engineer, Product Manager

    Notable Faculty: Yann LeCun (Convolutional neural networks, deep learning, AI); Kyunghyun Cho (Natural language processing, neural machine translation); Joan Bruna (Mathematical foundations of deep learning, geometric deep learning); Lerrel Pinto (Robotics, reinforcement learning, computer vision)

    Admissions: