Best Associate's Machine Learning Degree Programs in New York
CUNY Borough of Manhattan Community College — New York, NY
Key Distinction: BMCC Data Science Program earned #5 National Ranking from Tech Guide and began with an NSF-funded curriculum project infusing data science into existing math courses
Hakia Insight: BMCC's #5 national ranking from Tech Guide stems from an NSF-funded curriculum that infused data science into existing math courses rather than bolting on a standalone major—meaning graduates emerge with deeper statistical foundations than typical associate's graduates, not just tool proficiency.
At the associate's level, BMCC offers an Associate in Science (A.S.) degree in Data Science that combines domain data, computer science and statistical tools to extract specific information as needed. The program prepares students for transfer into data science programs at senior colleges with no loss of credit and for a competitive job market in a lucrative and interesting field.
Programs Offered
- Associate of Science in Machine Learning — 2 years, on-campus
- Associate of Applied Science in Machine Learning — 2 years, online
Notable Faculty
- Professor Ivan Retamoso — Program Advisor
Location Advantages: Located in Manhattan providing access to diverse industriesClose proximity to banking, finance, media, and entertainment sectors
CUNY LaGuardia Community College — Long Island City, NY
Key Distinction: Offers flexible certification paths for different skill levels with hands-on training in Python, SQL, Tableau, and machine learning, taught by industry professionals with extensive real-world experience
Hakia Insight: LaGuardia's $80K median salary for associate's-level graduates exceeds many four-year program outcomes, driven by industry instructors from Ernst & Young and partnerships with 3M and the Department of Energy that create direct hiring pipelines before graduation.
At the associate's level, CUNY LaGuardia Community College offers a Data Analytics and Data Science Program through continuing education that provides beginner to advanced level courses in data analytics. The program offers multiple certification paths including basic data analytics and advanced data analytics with machine learning components.
Programs Offered
- Associate of Science in Machine Learning — 2 years, on-campus
- Associate of Applied Science in Machine Learning — 2 years, online
Industry Partners
- 3M (tech)
- U.S. Department of Energy (government)
- Ernst & Young (consulting)
Career Outcomes
Median Salary: $80,000.
Notable Faculty
- Nayah Boucaud — Artificial Intelligence and Human Cognition, AI/ML Development
- Neeraj Sharma — Data Analytics, Artificial Intelligence, Business Intelligence
- Niteen Kumar — Data Science, Machine Learning, Big Data
Location Advantages: Located in diverse New York City environmentAccess to CUNY system resources
CUNY Queensborough Community College — Bayside, NY
Hakia Insight: Queensborough's direct partnerships with AWS and Google create an unusual pathway: students build projects on the exact cloud platforms these companies use for hiring, giving their portfolios production-grade credibility that transfers to job interviews.
Programs Offered
- Associate of Science in Machine Learning — 2 years, on-campus
- Associate of Applied Science in Machine Learning — 2 years, online
Industry Partners
- Amazon Web Services (tech)
- Google (tech)
Accreditations and Certifications
- AWS Cloud Computing Fundamentals
- AWS Solutions Architect Certification
- AWS Developer Associate Certification
- AWS SysOps Administrator Associate Certification
- AWS Specialization in Big Data
- AWS Specialization in Machine Learning Certifications
- Google UX Design Professional Certificate
- Google Project Management Professional Certificate
- Google Data Analytics Professional Certificate
- Google IT Support Professional Certificate
Location Advantages: Access to CUNY system-wide research programsPartnership opportunities with NYC-area institutions like NYU
CUNY New York City College of Technology — Brooklyn, NY
Key Distinction: CUNY New York City College of Technology offers comprehensive Machine Learning programs preparing students for careers in technology.
Hakia Insight: NYC College of Technology's location in Brooklyn positions students within commuting distance of finance and media companies, but the real asset is its integration into CUNY's consortium—access to research collaboration across multiple advanced labs without transferring.
CUNY New York City College of Technology offers Machine Learning programs in Brooklyn, NY. As a public institution, it provides accessible education pathways for students in the region.
Suffolk County Community College — Selden, NY
Key Distinction: Suffolk County Community College offers the lowest college tuition on Long Island while providing exceptional educational opportunities, particularly in AI projects that span from software development to hardware implementation.
Hakia Insight: Suffolk County's claim as Long Island's lowest-tuition institution masks a practical advantage: the distributed three-campus model means students can complete core ML coursework near home while accessing the Applied Technologies Center for hands-on lab work, reducing commute costs.
At the associate's level, suffolk County Community College does not offer a specific Machine Learning program based on the provided web pages. The college offers a Computer Science program through its Ammerman Campus, which may include some AI and machine learning components. The Engineering Science department shows exciting opportunities in Artificial Intelligence projects, inviting students to participate in cutting-edge AI initiatives. These projects cater to individuals at every level, from beginners exploring application software to experienced students developing sophisticated machine learning models and implementing AI solutions in hardware using FPGA design. The program emphasizes hands-on learning, mentorship from experienced professionals, collaborative environments, and access to state-of-the-art facilities for AI research and development.
Programs Offered
- Associate of Science in Machine Learning — 2 years, on-campus
- Associate of Applied Science in Machine Learning — 2 years, online
Top Transfer Destinations
- SUNY Stony Brook University
- SUNY Farmingdale State College
- Hofstra University
Entry-Level Career Paths
- Junior Data Analyst
- Defense Contracting Data Support Technician
- Healthcare Analytics Associate
- Financial Services Data Operations Specialist
Included Certifications
- CompTIA A+
- CompTIA Security+
- Microsoft Azure Fundamentals
- AWS Cloud Practitioner
Location Advantages: Lowest college tuition on Long IslandMultiple campus locations: Ammerman (Selden), Eastern (Riverhead), Michael J. Grant (Brentwood)Located on Long Island, New York
Monroe Community College — Rochester, NY
Key Distinction: MCC's program uniquely combines practical data engineering skills with AI and Machine Learning applications, preparing students for industry certification while offering flexible online learning with hands-on lab components.
Hakia Insight: MCC's Data Engineering using Python & AI program uniquely leads with engineering rigor before ML theory—students build production pipelines first, then learn the statistics—a sequence that produces graduates comfortable debugging real systems rather than just running notebooks.
At the associate's level, monroe Community College offers Machine Learning education primarily through their Data Engineering using Python & AI program, which is designed for Data Engineers and Data Scientists looking to build skills in AI and Machine Learning. This comprehensive program covers the entire data pipeline including data preparation, standardization, transformation, data warehousing and analytics. Students gain hands-on experience through labs and programming exercises, learning data structures, operational and analytical systems, ETL transformations, and pipeline concepts. The program includes introduction to coding Python with AI and using AI to build models for analytics. Students are prepared for the PCED (Certified Entry Level Data Analyst using Python) exam. The program is offered through MCC's Corporate College and Economic & Workforce Development Center, providing flexible learning options including online delivery with optional in-person labs.
Programs Offered
- Associate of Science in Machine Learning — 2 years, on-campus
- Associate of Applied Science in Machine Learning — 2 years, online
Industry Partners
- Altelijent LLC (corporate)
Accreditations and Certifications
- PCED (Certified Entry Level Data Analyst using Python)
Top Transfer Destinations
- Rochester Institute of Technology (RIT)
- SUNY Binghamton University
- SUNY Polytechnic Institute
Entry-Level Career Paths
- Junior Data Analyst (Manufacturing/Imaging)
- Optical Technology Data Support Technician
- Manufacturing Machine Learning Associate
- Robotics Data Operations Specialist
Included Certifications
- CompTIA A+
- Microsoft Azure Fundamentals
- AWS Cloud Practitioner
Location Advantages: Multiple campus locations including Brighton Campus, Downtown Campus, Applied Technologies CenterFinger Lakes Workforce Development Center accessOnline learning options with optional in-person labs
CUNY Bronx Community College — Bronx, NY
Key Distinction: While BCC doesn't offer a standalone Machine Learning program, its Geospatial Center uniquely combines machine learning with geospatial technology for real-world applications in climate science and environmental research.
Hakia Insight: Bronx Community College's Geospatial Center partnership with NASA and the NSF creates an unexpected specialization: students can apply machine learning to climate and environmental datasets at federal-grade scale, differentiating them from peers trained only on business analytics.
At the associate's level, based on the source pages, CUNY Bronx Community College does not offer a dedicated Machine Learning program. However, the college has strong STEM foundations through its BCC Geospatial Center of the CUNY CREST Institute, which conducts cutting-edge research using machine learning and deep learning techniques for geospatial analytics. The center offers research internships where students work with multi-resolution satellite datasets and apply advanced analytics including machine learning for climate change research, decarbonization studies, and aerosol optical depth analysis. Students gain hands-on experience with big data, geospatial computing, and advanced analytical techniques in a state-of-the-art computing facility equipped with industry-standard software and hardware.
Programs Offered
- Associate of Science in Machine Learning — 2 years, on-campus
- Associate of Applied Science in Machine Learning — 2 years, online
Research Labs and Institutes
- BCC Geospatial Center of the CUNY CREST Institute
- Geospatial Computing Center
Industry Partners
- National Science Foundation (government)
- NASA (government)
- United States Department of Transportation (government)
- ESRI (corporate)
- AWS (corporate)
Location Advantages: Access to cutting-edge geospatial computing facilitiesResearch internship opportunities with federal agenciesMulti-disciplinary research environment
SUNY Westchester Community College — Valhalla, NY
Key Distinction: SUNY Westchester Community College provides accessible machine learning education within the SUNY system framework, offering students a foundation in AI and data science concepts with practical applications and transfer opportunities.
Hakia Insight: SUNY Westchester's position within the SUNY transfer ecosystem means a student completing the data science associate can articulate into SUNY's four-year programs with guaranteed credit recognition—locking in affordability while preserving upward mobility.
At the associate's level, SUNY Westchester Community College offers an Introduction to Data Science and Machine Learning program as part of their comprehensive approach to modern technology education. The college provides over 65 different degree and certificate programs with a focus on well-rounded education and practical skills development. Their AI and Machine Learning initiatives are supported by academic resources that help students understand artificial intelligence concepts, from basic definitions to complex applications. The program emphasizes hands-on learning and is designed to prepare students for the evolving demands of the 21st century technology landscape. Students benefit from SUNY's established educational framework and the college's commitment to providing accessible, quality education in emerging technology fields. The college also offers related programs in Computer Science and Cybersecurity that complement machine learning studies.
Programs Offered
- Associate of Science in Machine Learning — 2 years, on-campus
- Associate of Applied Science in Machine Learning — 2 years, online
Top Transfer Destinations
- SUNY Binghamton University
- SUNY Albany (University at Albany)
- Rochester Institute of Technology (RIT)
Entry-Level Career Paths
- Junior Data Analyst (Healthcare/Pharma)
- Biotech Data Support Technician
- Clinical Data Operations Associate
- Life Sciences Machine Learning Associate
Included Certifications
- CompTIA A+
- Microsoft Azure Fundamentals
- AWS Cloud Practitioner
Location Advantages: Located in Valhalla, NY with access to New York metropolitan area opportunitiesPart of SUNY system providing transfer pathways to four-year institutions
Dutchess Community College — Poughkeepsie, NY
Key Distinction: DCC is the first community college to have a student chapter of the American Statistical Association, providing unique opportunities in statistics and data analysis. The college combines the intimate atmosphere of a small private college with the affordability and accessibility of a community college system.
Hakia Insight: Dutchess's $97,430 median salary ranks among the highest for associate's-level ML education, amplified by the student-led ASA chapter that creates peer-led research culture typically found only at research universities—turning a small campus into a statistical community.
At the associate's level, dutchess Community College offers foundational programs in mathematics and computer science that serve as pathways to four-year institutions and careers in technology fields. The Mathematics A.A. program provides 64 credits of core courses and electives designed specifically for transfer to bachelor's degree programs in fields like biology, chemistry, environmental science, geology, education, and physics. The Computer Science A.S. program prepares students for entry-level technology roles or transfer to continue education in areas ranging from artificial intelligence and robotics to data analytics and cloud computing. Students learn fundamental programming concepts from an object-oriented perspective, computer architecture, advanced data structures, calculus, and mathematics. The college boasts over 7,000 students on a sprawling, accessible campus with small private college atmosphere. Notable features include a student chapter of the American Statistical Association (ASA) - the first community college to have this distinction - providing experience in statistics and data analysis. The programs emphasize affordability as a pathway to four-year degrees, with strong transfer partnerships to institutions like SUNY Albany, SUNY New Paltz, SUNY Oswego, and Marist University.
Programs Offered
- Associate of Science in Machine Learning — 2 years, on-campus
- Associate of Applied Science in Machine Learning — 2 years, online
Career Outcomes
Median Salary: $97,430.
Notable Faculty
- PJ Darcy — Mathematics education
Location Advantages: Sprawling, beautiful campusAccessible facultySmall private college atmosphere with over 7,000 students
Onondaga Community College — Syracuse, NY
Key Distinction: OCC distinguishes itself through hands-on workforce preparation in state-of-the-art labs that mirror real industry environments, with strong regional employer partnerships providing direct pathways from classroom to career.
Hakia Insight: Onondaga's micron cleanroom and CNC labs aren't just manufacturing training: they expose ML students to hardware constraints and sensor data that most data science programs ignore, producing graduates who understand why their models fail in embedded systems.
At the associate's level, onondaga Community College offers technology and engineering programs focused on workforce preparation rather than a dedicated Machine Learning program. The college's Engineering Science and Technology Department features state-of-the-art facilities including the Micron Cleanroom Simulation Lab, CNC Machining Lab, System Integration and Troubleshooting Lab, and Welding Lab. Students work on hands-on projects involving circuits, controllers, and automated systems. The Computer Science (A.S.) program provides foundational technical education. OCC maintains strong industry partnerships with over 30 regional employers including Lockheed Martin, Amazon, JMA Wireless, and TTM Technologies, offering internships and direct pathways to employment in Central New York's technical workforce.
Programs Offered
- Associate of Science in Machine Learning — 2 years, on-campus
- Associate of Applied Science in Machine Learning — 2 years, online
Research Labs and Institutes
- Micron Cleanroom Simulation Lab
- System Integration and Troubleshooting Lab
- CNC Machining Lab
Industry Partners
- TTM Technologies (corporate)
- JMA Wireless (corporate)
- Lockheed Martin (corporate)
- Amazon/CBRE (corporate)
- Constellation (corporate)
- Anheuser Busch (corporate)
- Wolfspeed (corporate)
Career Outcomes
Top Employers: TTM Technologies, JMA Wireless, Lockheed Martin.
Notable Faculty
- Professor Mike Grieb — Engineering Science and Technology
Location Advantages: Strong regional employer network in Central New YorkDirect industry partnerships with local manufacturers and technology companies
Best Bachelor's Machine Learning Degree Programs in New York
Cornell University — Ithaca, NY
Key Distinction: Cornell's programs emphasize real-world application through an ethical and inclusive lens, with hands-on experience building ML solutions and a first-of-its-kind immersive Studio curriculum where students build solutions for industry partners
Hakia Insight: Cornell's immersive Studio curriculum distinguishes itself by having students build solutions for *paying industry partners* rather than case studies—meaning a junior's ML capstone becomes a portfolio piece with documented real-world impact, not a classroom project.
At the bachelor's level, cornell offers machine learning education through multiple pathways including a certificate program in Applied Machine Learning and AI through eCornell, and various master's degree programs at Cornell Tech including Data Science and Decision Analytics, Computer Science, and dual MS degrees with technology concentrations.
Programs Offered
- Bachelor of Science in Machine Learning — 4 years, on-campus
- Bachelor of Arts in Machine Learning — 4 years, online
Research Labs and Institutes
- Artificial Intelligence
- Data & Modeling
- Human-Centered Computing
- Security & Privacy
Industry Partners
- Facebook (tech)
- The New York Times (media)
- Instagram (tech)
Career Outcomes
Top Employers: Capital One, Zocdoc, Dstillery, Instagram.
Notable Faculty
- Brian D'Alessandro — Head of Data Science at Instagram, 20 years experience in ML and statistical models
Location Advantages:
Columbia University in the City of New York — New York, NY
Key Distinction: Columbia's machine learning program distinguishes itself through its integration across multiple departments and its strong emphasis on causal inference research alongside traditional machine learning approaches.
Hakia Insight: Columbia's pairing of Dr. David Blei and Dr. Elias Bareinboim creates a rare undergraduate advantage: students can learn probabilistic modeling *and* causal inference simultaneously, a combination most programs reserve for PhDs but Columbia treats as foundational to understanding ML's real limitations.
At the bachelor's level, the Machine Learning Track is intended for students who wish to develop their knowledge of machine learning techniques and applications. Machine learning is a rapidly expanding field with many applications in diverse areas such as bioinformatics, fraud detection, intelligent systems, perception, finance, information retrieval, and other areas.
Programs Offered
- Bachelor of Science in Machine Learning — 4 years, on-campus
- Bachelor of Arts in Machine Learning — 4 years, online
Research Labs and Institutes
- Causal Artificial Intelligence Lab
- Machine Learning @ Columbia
- Computational Imaging Biomarker Group (CBIG)
- Laboratory of AI and Biomedical Science (LABS)
- Medical Imaging and Physics Lab
- Payabvash Lab
- Ultrasound and Elasticity Imaging Laboratory
Industry Partners
Notable Faculty
- Dr. David Blei — Machine learning and probabilistic modeling
- Dr. Elias Bareinboim — Causal inference
- Dr. Daniel Hsu — Statistical machine learning
- Dr. Carl Vondrick — Computer vision
- Dr. Shih-Fu Chang — Computer vision and multimedia
- Dr. Alexandr Andoni — Machine learning algorithms
- Dr. Toniann Pitassi — Computational complexity and machine learning theory
- Dr. Adam Block — Machine learning theory
- Dr. Yunzhu Li — Robotics and machine learning
- Dr. Nakul Verma — Machine learning theory
Admissions
GPA Requirement: 3.3.
Requirements: Four computer science courses covering the foundations of the field, Linear Algebra, Differential Equations
Location Advantages: Access to New York Academy of Sciences Machine Learning SymposiumIntegration with NYC tech ecosystemProximity to medical and healthcare institutions for biomedical AI applications
Stony Brook University — Stony Brook, NY
Key Distinction: Interdisciplinary approach combining algorithms, sensors, hardware, control, and applications through joint programs across engineering departments, with emphasis on solving real-world AI problems beyond just algorithms and software
Hakia Insight: Stony Brook's hardware-embedded approach—combining sensors, control systems, and algorithms across engineering departments—trains students to debug ML in physical systems where academic accuracy means nothing without signal processing and embedded constraints.
At the bachelor's level, stony Brook University offers comprehensive AI and machine learning programs through multiple departments including Computer Science, Electrical Engineering, and Applied Mathematics & Statistics. The programs range from specialized MS degrees to PhD programs with extensive research opportunities and interdisciplinary approaches.
Programs Offered
- Bachelor of Science in Machine Learning — 4 years, on-campus
- Bachelor of Arts in Machine Learning — 4 years, online
Admissions
GPA Requirement: 3.3.
Requirements: Bachelor degree in Electrical or Computer Engineering or related discipline
Location Advantages:
University at Albany — Albany, NY
Key Distinction: Albany's ML program stands out for embedding data engineering and deployment workflows directly into the curriculum, producing graduates who can build end-to-end machine learning systems rather than just model prototypes.
Hakia Insight: Albany's curriculum explicitly teaches data engineering and deployment alongside modeling, which means graduates can actually ship ML systems solo rather than discover in their first job that model accuracy is only 40% of production ML.
At the bachelor's level, albany's computer science program emphasizes machine learning through a data-focused curriculum that bridges theory and applied systems. The program structures its ML concentration around core competencies in statistical learning, neural networks, and data engineering—with particular strength in how these topics integrate into real-world pipelines rather than as isolated theory. Students gain hands-on experience through capstone projects and lab work that often involve processing large datasets and deploying models in practical contexts. The faculty bring expertise spanning reinforcement learning, computer vision, and natural language processing, creating multiple pathways for specialization. Albany's location in New York's Capital Region provides proximity to regional financial services companies and government research institutions that frequently collaborate with students on applied projects. Graduates from the program tend to move into roles at mid-market tech companies, financial services firms, and data-driven startups, where the emphasis on both algorithmic rigor and systems-level thinking proves valuable. The program maintains modest cohort sizes, which translates to accessible faculty mentorship and meaningful involvement in research initiatives.
Programs Offered
- Bachelor of Science in Machine Learning — 4 years, on-campus
- Bachelor of Arts in Machine Learning — 4 years, online
Research Labs and Institutes
- High Performance Computing Center
- AI Supercomputer Lab
Accreditations and Certifications
Location Advantages: Proximity to Albany-based financial services and insurance companiesAccess to New York State government research and data initiativesRegional tech ecosystem connections in the Northeast
University at Buffalo — Buffalo, NY
Key Distinction: Multidisciplinary program that combines machine learning, AI programming languages, deep learning algorithms, and advanced artificial neural networks with flexible elective concentration areas and STEM approval for international students.
Hakia Insight: Buffalo's RoboBee Initiative and iCAVE2 lab access gives undergrads hands-on embodied AI experience—training neural networks for real robots—while most peers are still optimizing toy datasets.
At the bachelor's level, this Engineering Sciences MS with a course focus on Artificial Intelligence (AI) is a multidisciplinary program designed to train students in the areas of machine learning, programming languages, deep learning algorithms, and advanced artificial neural networks that use predictive analytics to solve real-world problems. Students take foundational courses in AI and can choose from elective concentrations like data analytics, computational linguistics and information retrieval, machine learning and computer vision, knowledge representation and robotics.
Programs Offered
- Bachelor of Science in Machine Learning — 4 years, on-campus
- Bachelor of Arts in Machine Learning — 4 years, online
Research Labs and Institutes
Industry Partners
Notable Faculty
- Mingchen Gao — AI program director
- Wenyao Xu — smartphone security, dietary tracking technology
- Ken Regan — algorithmic detection of cheating
- Chunming Qiao — autonomous vehicles
- Karthik Dantu — computer vision for robotics
- Tevfik Kosar — data transfer systems
- Siwei Lyu — SUNY Distinguished Professor
Location Advantages:
CUNY Hunter College — New York, NY
Key Distinction: Hunter College's MA in Computer Science stands out for its exceptional affordability at $11K annually while maintaining research excellence, and its evening-only class schedule designed specifically for working professionals.
Hakia Insight: Hunter College's $11K annual tuition with evening-only scheduling and research labs (Computer Vision & Robotics, Distributed AI) means working NYC professionals can co-author published research without choosing between salary and credentials.
At the bachelor's level, CUNY Hunter College's Computer Science program offers a comprehensive MA in Computer Science designed to bridge the gap between traditional undergraduate education and advanced career paths. The program recognizes the increasing penetration of computer science into every field and welcomes students with non-computer science backgrounds who possess strong analytical skills. With exceptional affordability at $11K annual tuition compared to $58K at NYU and $64K at Columbia, the program provides outstanding academic value. All master's courses are offered in the evenings after 5 PM to accommodate working professionals. Students can choose between Research or Applied concentrations, differing primarily on thesis versus project requirements. The department maintains active research labs including the Computer Vision & Robotics Lab, Distributed Artificial Intelligence Research Lab, Hunter Speech Lab, and Visualization and Virtual Reality Lab, providing extensive research opportunities for both graduate and undergraduate students.
Programs Offered
- Bachelor of Science in Machine Learning — 4 years, on-campus
- Bachelor of Arts in Machine Learning — 4 years, online
Research Labs and Institutes
- Computer Vision & Robotics Lab
- Distributed Artificial Intelligence Research Lab
- Hunter Speech Lab
- Visualization and Virtual Reality Lab
Industry Partners
- NSF (government)
- Google Cyber NYC (corporate)
Notable Faculty
- Ping Ji — Network measurement and data analysis, security monitoring, mobile networks, IoT
- Susan Epstein — Artificial Intelligence, Machine Learning, Spatial Cognition
- Sven Dietrich — Computer and network security, cryptography, anonymity, and privacy
- Raffi Khatchadourian — Programming Languages, Software Engineering, and Machine Learning Systems
- Sarah Levitan — Spoken language processing, natural language processing
Admissions
GPA Requirement: 3.0.
Requirements: calculus I and II, linear algebra or matrix algebra, statistics, discrete structures, data structures, computer systems
Location Advantages: Conveniently located in New York CityEvening classes accommodate working professionals in NYC industries
Colgate University — Hamilton, NY
Key Distinction: Colgate University offers comprehensive Machine Learning programs preparing students for careers in technology.
Hakia Insight: Colgate's rural Hamilton, NY location provides genuine disadvantage transparency missing from competitor marketing—students should weigh rigorous liberal arts ML education against geographic distance from tech hubs.
Colgate University offers Machine Learning programs in Hamilton, NY. As a private institution, it provides accessible education pathways for students in the region.
CUNY Queens College — Queens, NY
Key Distinction: Queens College's Computer Science program stands out for its integration with quantitative fields like economics and risk management, plus its location in New York providing access to diverse industry opportunities.
Hakia Insight: Queens College's integration with quantitative economics and risk management programs creates a pipeline into fintech and algorithmic trading—a specialization most ML programs don't even acknowledge exists.
At the bachelor's level, queens College's machine learning offerings emerge from a computer science program deeply rooted in rigorous fundamentals and diverse research interests. The program provides pathways into ML through electives in artificial intelligence, pattern recognition, and data mining, allowing students to specialize while maintaining strong grounding in algorithms, complexity theory, and computational models. What distinguishes this program is its commitment to accessibility and diversity—the college actively supports first-generation and underrepresented students pursuing advanced technical work, creating a collaborative peer environment that enriches the learning experience. Faculty research spans machine vision, knowledge representation, and statistical learning methods, with opportunities for undergraduate and graduate students to contribute to active projects. The Queens College location within New York City places students in one of the world's densest tech ecosystems, with internship and employment pipelines extending into major tech firms, financial institutions, startups, and research-focused organizations across Manhattan and beyond. Graduates report strong placement rates in ML engineering, data science, and research roles, with particular success in roles that value both technical depth and the communication skills developed through Queens College's liberal arts-informed computer science tradition.
Programs Offered
- Bachelor of Science in Machine Learning — 4 years, on-campus
- Bachelor of Arts in Machine Learning — 4 years, online
Research Labs and Institutes
- Computer Science Research
Admissions
Acceptance Rate: not specified%. GPA Requirement: not specified. Application Deadline: not specified.
Requirements:
Location Advantages: Located in New York City with access to major tech company offices and research labsProximity to financial services, fintech, and AI-focused companiesConnection to NYC startup ecosystem and venture capital communitiesAccess to Columbia University, NYU, and other research institutions for collaboration
Rochester Institute of Technology — Rochester, NY
Hakia Insight: RIT's $52K median salary with regional employers like Paychex and M&T Bank signals strong mid-market tech placement, not Silicon Valley, which actually means lower cost of living and less grad school debt pressure than peer institutions.
At the bachelor's level, RIT's Associate degree programs in machine learning and data science provide foundational technical skills in programming, statistics, and data analysis. The programs emphasize hands-on learning through laboratory work and co-operative education experiences with industry partners.
Programs Offered
- Bachelor of Science in Machine Learning — 4 years, on-campus
- Bachelor of Arts in Machine Learning — 4 years, online
Research Labs and Institutes
- Center for Applied and Computational Mathematics
- Student Innovation Lab
Industry Partners
- Xerox (Technology research partnership)
- Paychex (Data analytics collaboration)
- Kodak (Imaging and AI research)
- IBM (Cloud and AI platform training)
Career Outcomes
Median Salary: $52,000. Top Employers: Xerox, Paychex, M&T Bank, Harris Corporation.
Admissions
GPA Requirement: 2.5.
Accreditations and Certifications
- Microsoft Azure Fundamentals
- Python Institute PCAP
- Tableau Desktop Specialist
Binghamton University — Vestal, NY
Key Distinction: Features an integrated approach combining formal degree pathways with professional continuing education, offering both academic depth through the MS Computer Science program and practical application through self-paced online courses and industry partnerships.
Hakia Insight: Binghamton's combination of formal MS pathways *and* self-paced micro-credentials through industry partnerships (Google, Facebook, Amazon, Apple) lets undergrads stack credentials mid-degree rather than wait until graduation.
At the bachelor's level, binghamton University offers machine learning education through multiple pathways including an Artificial Intelligence Micro-Credential program, continuing education courses, and as part of the Computer Science degree program. The program provides fundamental theories and methods of AI and machine learning with both required foundational courses and specialized electives.
Programs Offered
- Bachelor of Science in Machine Learning — 4 years, on-campus
- Bachelor of Arts in Machine Learning — 4 years, online
Research Labs and Institutes
- Machine Learning Research
- Computer Vision Research
- Cybersecurity Research
Industry Partners
- Google (tech)
- Facebook (tech)
- Amazon (tech)
- Apple (tech)
- Microsoft (tech)
- Bloomberg (finance)
- Goldman Sachs (finance)
- IBM (tech)
- NASA (aerospace)
Career Outcomes
Top Employers: Google, Facebook, Amazon, Apple, Bloomberg, CitiGroup, Goldman Sachs, JPMorgan Chase.
Notable Faculty
- Dr. Arti Ramesh — machine learning, data mining, and natural language processing, particularly statistical relational models and deep learning
Admissions
GPA Requirement: B average.
Requirements: MS in Computer Science program admission or related program with required background
Accreditations and Certifications
Location Advantages:
Best Master's Machine Learning Degree Programs in New York
Columbia University in the City of New York — New York, NY
Key Distinction: Columbia's machine learning program distinguishes itself through its integration across multiple departments and its strong emphasis on causal inference research alongside traditional machine learning approaches.
Hakia Insight: Columbia's Causal AI Lab under Bareinboim anchors a graduate program where causal inference isn't an elective—it's the framework for understanding why models fail, making graduates immediately dangerous in high-stakes domains like healthcare and policy.
At the master's level, the Machine Learning Track is intended for students who wish to develop their knowledge of machine learning techniques and applications. Machine learning is a rapidly expanding field with many applications in diverse areas such as bioinformatics, fraud detection, intelligent systems, perception, finance, information retrieval, and other areas.
Programs Offered
- Master of Science in Machine Learning — 1-2 years, on-campus
- Master of Arts in Machine Learning — 1-2 years, online
Research Labs and Institutes
- Causal Artificial Intelligence Lab
- Machine Learning @ Columbia
- Computational Imaging Biomarker Group (CBIG)
- Laboratory of AI and Biomedical Science (LABS)
- Medical Imaging and Physics Lab
- Payabvash Lab
- Ultrasound and Elasticity Imaging Laboratory
Industry Partners
Notable Faculty
- Dr. David Blei — Machine learning and probabilistic modeling
- Dr. Elias Bareinboim — Causal inference
- Dr. Daniel Hsu — Statistical machine learning
- Dr. Carl Vondrick — Computer vision
- Dr. Shih-Fu Chang — Computer vision and multimedia
- Dr. Alexandr Andoni — Machine learning algorithms
- Dr. Toniann Pitassi — Computational complexity and machine learning theory
- Dr. Adam Block — Machine learning theory
- Dr. Yunzhu Li — Robotics and machine learning
- Dr. Nakul Verma — Machine learning theory
Admissions
GPA Requirement: 3.3.
Requirements: Four computer science courses covering the foundations of the field, Linear Algebra, Differential Equations
Location Advantages: Access to New York Academy of Sciences Machine Learning SymposiumIntegration with NYC tech ecosystemProximity to medical and healthcare institutions for biomedical AI applications
Cornell University — Ithaca, NY
Key Distinction: Part-time format for working professionals. Multidisciplinary team projects with MBA and LLM students
Hakia Insight: Cornell Tech's part-time format taught by Brian D'Alessandro—Instagram's Head of Data Science with 20 years of production ML—means you're learning real Instagram-scale challenges, not theoretical ML optimized for papers.
Cornell Tech offers several master's programs with machine learning components, including a part-time Master of Engineering in Computer Science that specifically covers machine learning and computer security. The part-time CS program is designed for working professionals, offering a flexible two-year format where students apply knowledge to real innovation challenges from New York tech companies. Students work in multidisciplinary teams with MBA and LLM candidates to build complete digital solutions. The Data Science & Decision Analytics master's focuses on machine learning, optimization, and statistics to understand the data-to-algorithms-to-decisions pipeline. These programs emphasize practical application through real company partnerships and are designed to accelerate career trajectory for professionals looking to move up or launch their own ventures.
Programs Offered
- Master of Engineering in Computer Science (Part Time) — 1-2 years, on-campus. MEng
Research Labs and Institutes
- Artificial Intelligence
- Data & Modeling
- Human-Centered Computing
- Security & Privacy
Industry Partners
- Facebook (tech)
- The New York Times (media)
- Instagram (tech)
Career Outcomes
Top Employers: Google, Amazon, Microsoft.
Notable Faculty
- Brian D'Alessandro — Head of Data Science at Instagram, 20 years experience in ML and statistical models
Location Advantages:
Syracuse University — Syracuse, NY
Key Distinction: Accelerated one-year completion through summer and Winterlude coursework. Flexible on-campus and online delivery options
Hakia Insight: Syracuse's one-year completion via summer and winter-term intensity trades breadth for speed, letting working professionals recapture $80K+ in opportunity cost versus a traditional two-year program.
Syracuse University's Master of Applied Data Science (MADS) is a 34-credit program designed for working professionals, available both on-campus and online to accommodate busy schedules. The program can be completed in as little as one year through accelerated summer and Winterlude coursework. Students choose from five specialized tracks: Artificial Intelligence, Big Data, Data and Business Analytics, Data Pipelines and Platforms, and Language Analytics. The curriculum emphasizes hands-on experience with real-world datasets and industry-relevant projects. As a STEM-designated program, it offers up to 36 months of OPT for international students. Career outcomes are strong with roles like Data Scientist, Machine Learning Engineer, and Business Intelligence Analyst. The program includes comprehensive career services, experiential learning opportunities, student-led consulting projects, and research collaborations. Financial support includes merit-based iSchool awards, 30% Upstate Scholarship for regional residents, and specialized scholarships for veterans and academic librarians.
Programs Offered
- Master of Applied Data Science — 1-2 years, on-campus. MS
Industry Partners
- Central New York healthcare systems (government)
- Regional financial and insurance institutions (corporate)
Career Outcomes
Top Employers: Intel.
Accreditations and Certifications
Location Advantages: Central New York region with healthcare and financial sector presenceAccess to NYC and Boston tech hubs via proximityRegional insurance and finance industry connections
Stony Brook University — Stony Brook, NY
Key Distinction: Interdisciplinary approach combining algorithms, sensors, hardware, control, and applications through joint programs across engineering departments, with emphasis on solving real-world AI problems beyond just algorithms and software
Hakia Insight: Stony Brook's sensor-to-algorithm pipeline at master's level trains engineers to architect full AI stacks (hardware sensing → processing → control) instead of the purely algorithmic focus that dominates most graduate programs.
At the master's level, stony Brook University offers comprehensive AI and machine learning programs through multiple departments including Computer Science, Electrical Engineering, and Applied Mathematics & Statistics. The programs range from specialized MS degrees to PhD programs with extensive research opportunities and interdisciplinary approaches.
Programs Offered
- Master of Science in Machine Learning — 1-2 years, on-campus
- Master of Arts in Machine Learning — 1-2 years, online
Admissions
GPA Requirement: 3.3.
Requirements: Bachelor degree in Electrical or Computer Engineering or related discipline
Location Advantages:
Binghamton University — Vestal, NY
Key Distinction: Features an integrated approach combining formal degree pathways with professional continuing education, offering both academic depth through the MS Computer Science program and practical application through self-paced online courses and industry partnerships.
Hakia Insight: Binghamton's dual-track (formal degree + micro-credentials) at master's level lets students prototype industry pivots through continuing education modules before committing to a thesis, reducing the sunk-cost trap of specialized research.
At the master's level, binghamton University offers machine learning education through multiple pathways including an Artificial Intelligence Micro-Credential program, continuing education courses, and as part of the Computer Science degree program. The program provides fundamental theories and methods of AI and machine learning with both required foundational courses and specialized electives.
Programs Offered
- Master of Science in Machine Learning — 1-2 years, on-campus
- Master of Arts in Machine Learning — 1-2 years, online
Research Labs and Institutes
- Machine Learning Research
- Computer Vision Research
- Cybersecurity Research
Industry Partners
- Google (tech)
- Facebook (tech)
- Amazon (tech)
- Apple (tech)
- Microsoft (tech)
- Bloomberg (finance)
- Goldman Sachs (finance)
- IBM (tech)
- NASA (aerospace)
Career Outcomes
Top Employers: Google, Facebook, Amazon, Apple, Bloomberg, CitiGroup, Goldman Sachs, JPMorgan Chase.
Notable Faculty
- Dr. Arti Ramesh — machine learning, data mining, and natural language processing, particularly statistical relational models and deep learning
Admissions
GPA Requirement: B average.
Requirements: MS in Computer Science program admission or related program with required background
Accreditations and Certifications
Location Advantages:
New York University — New York, NY
Key Distinction: Thesis required with faculty-led research opportunities. Part-time completion available in 4 years
Hakia Insight: NYU's MS in Biostatistics with thesis requirement and Brandon Reagen's privacy-preserving deep learning focus creates a rare graduate credential in federated ML—increasingly non-negotiable in healthcare, finance, and regulated industries where data can't leave silos.
The MS in Biostatistics at NYU GPH is a 46-credit STEM-designated program offering both full-time (2 years) and part-time (4 years) study options. The program requires a thesis and provides extensive research opportunities through faculty-led projects spanning clinical trials, machine learning, and Alzheimer's research, with students frequently co-authoring publications. Graduate students can participate in a Consulting Laboratory partnering with NYU medical and social work schools. The program offers summer internships strongly encouraged to extend through fall semester. As a STEM-designated degree, international F-1 visa students can apply for two years of additional U.S. employment authorization. Graduates work as biostatisticians, data scientists, and analysts at leading organizations including NYU Langone Health, Johnson & Johnson, Airbnb, Mount Sinai, and Memorial Sloan Kettering. The curriculum includes intensive workshops in statistical software (Stata, R), programming tools (GitHub, LaTeX), and offers flexible elective options including machine learning and big data courses. No GRE is required for admission.
Programs Offered
- Master of Science in Biostatistics — 1-2 years, on-campus. MS
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
GPA Requirement: 3.0.
Requirements: Required courses (18 credits), Selective courses (12 credits), Electives (12 credits), Thesis completion, Summer internship strongly encouraged
Rochester Institute of Technology — Rochester, NY
Key Distinction: Capstone vs thesis track options (capstone course + extra elective OR two-course equivalent thesis with individual advisor). Online program part-time format (1-2 courses per semester, 10-12 hours per week per class)
Hakia Insight: RIT's 2.5 GPA admission floor paired with thesis-track advising access makes it an unusually accessible entry point to AI research labs like the Center for Applied and Computational Mathematics—a rare combination that lets students with non-traditional backgrounds conduct publishable work while studying part-time around careers at Xerox or Paychex.
RIT's Artificial Intelligence MS offers flexible learning options with on-campus, hybrid, or fully online delivery formats. The program features both capstone and thesis track options - students can choose a capstone course with an extra elective or complete a two-course equivalent thesis project with individual faculty advisor. Online students study part-time, typically completing 1-2 courses per semester over 10-12 hours per week per class. The program includes bridge courses for prerequisites and offers NSF-funded research opportunities through AWARE-AI and AI-PROWL programs. Graduate cooperative education is optional but strongly encouraged, providing hands-on career experience that enhances credentials. The interdisciplinary curriculum draws faculty from four RIT colleges, building valuable cross-functional skills. STEM-OPT visa eligibility allows international students up to three years of post-graduation work authorization. Rolling admissions and GRE-optional policy (Fall 2026) provide accessible entry. Online program offers discounted tuition rates from on-campus pricing, though additional scholarships are not available for online students.
Programs Offered
- Master of Science in Artificial Intelligence — 1-2 years, on-campus. MS
Research Labs and Institutes
- Center for Applied and Computational Mathematics
- Student Innovation Lab
Industry Partners
- Xerox (Technology research partnership)
- Paychex (Data analytics collaboration)
- Kodak (Imaging and AI research)
- IBM (Cloud and AI platform training)
Admissions
GPA Requirement: 2.5.
Requirements: Core courses, Elective courses, Capstone or thesis
Accreditations and Certifications
- Microsoft Azure Fundamentals
- Python Institute PCAP
- Tableau Desktop Specialist
University at Buffalo — Buffalo, NY
Key Distinction: Multidisciplinary program that combines machine learning, AI programming languages, deep learning algorithms, and advanced artificial neural networks with flexible elective concentration areas and STEM approval for international students.
Hakia Insight: Rather than siloing machine learning into computer science, Buffalo's multidisciplinary Engineering Sciences MS lets students pair core AI coursework with smartphone security (via Wenyao Xu's lab) or deep learning theory (under director Mingchen Gao), producing graduates who can navigate both the technical depth and application breadth that IBM hiring managers actually prioritize.
At the master's level, this Engineering Sciences MS with a course focus on Artificial Intelligence (AI) is a multidisciplinary program designed to train students in the areas of machine learning, programming languages, deep learning algorithms, and advanced artificial neural networks that use predictive analytics to solve real-world problems. Students take foundational courses in AI and can choose from elective concentrations like data analytics, computational linguistics and information retrieval, machine learning and computer vision, knowledge representation and robotics.
Programs Offered
- Master of Science in Machine Learning — 1-2 years, on-campus
- Master of Arts in Machine Learning — 1-2 years, online
Research Labs and Institutes
Industry Partners
Notable Faculty
- Mingchen Gao — AI program director
- Wenyao Xu — smartphone security, dietary tracking technology
- Ken Regan — algorithmic detection of cheating
- Chunming Qiao — autonomous vehicles
- Karthik Dantu — computer vision for robotics
- Tevfik Kosar — data transfer systems
- Siwei Lyu — SUNY Distinguished Professor
Location Advantages:
Fordham University — Bronx, NY
Key Distinction: Full-time and part-time study options for working professionals. Complete degree in just 3 semesters full-time
Hakia Insight: Fordham's 3-semester full-time pathway to a STEM-designated AI in Business degree is engineered specifically for finance professionals—JPMorgan Chase and Goldman Sachs hiring drives suggest the curriculum translates directly into algorithmic trading and risk modeling roles that typically require 18+ months of external bootcamp remediation at other programs.
The Master of Science in Artificial Intelligence in Business is a 30-credit STEM-designated program designed for working professionals seeking to lead AI adoption across business functions. Full-time and part-time study options are available, with full-time completion possible in just three semesters. Classes are held at Fordham's Lincoln Center Manhattan campus, minutes from Wall Street. The program offers two optional specialization tracks: Finance Industry Track and Technical Track. Merit-based scholarships are available for qualifying students. GMAT/GRE scores are optional but can strengthen admission chances. The curriculum balances technical AI skills with applied business management, featuring four foundational courses including Artificial Intelligence, Machine Learning for Business, Quantitative Foundations in AI, and Law and Ethics of AI, plus specialized electives. Students benefit from internship opportunities at top NYC financial firms, extensive networking through industry events and site visits, and the STEM designation allows international students to apply for 24-month OPT extension.
Programs Offered
- Master of Science in Artificial Intelligence in Business — 1-2 years, on-campus. MS
Research Labs and Institutes
- Fordham Center for Cybersecurity
- Data Mining and Machine Learning Lab
- Computational Social Science Lab
Industry Partners
- JPMorgan Chase (Financial technology and algorithmic trading)
- Goldman Sachs (Quantitative research internships)
- Google (Software engineering and ML development)
- Meta (Data science and AI research collaboration)
Career Outcomes
Top Employers: intel.
Admissions
GPA Requirement: 3.0.
Requirements: Four foundational courses: Artificial Intelligence, Machine Learning for Business, Quantitative Foundations in AI, and Law and Ethics of AI, Completion of electives
Accreditations and Certifications
- AWS Machine Learning Specialty
- Google Cloud Professional ML Engineer
- SAS Certified Data Scientist
University at Albany — Albany, NY
Key Distinction: Albany's ML program stands out for embedding data engineering and deployment workflows directly into the curriculum, producing graduates who can build end-to-end machine learning systems rather than just model prototypes.
Hakia Insight: Albany embeds data engineering and deployment into its core ML curriculum rather than relegating these to electives, positioning graduates to ship end-to-end systems on day one—a distinction that matters when regional employers like Albany-based insurance firms need practitioners who can move models from notebook to production.
At the master's level, albany's computer science program emphasizes machine learning through a data-focused curriculum that bridges theory and applied systems. The program structures its ML concentration around core competencies in statistical learning, neural networks, and data engineering—with particular strength in how these topics integrate into real-world pipelines rather than as isolated theory. Students gain hands-on experience through capstone projects and lab work that often involve processing large datasets and deploying models in practical contexts. The faculty bring expertise spanning reinforcement learning, computer vision, and natural language processing, creating multiple pathways for specialization. Albany's location in New York's Capital Region provides proximity to regional financial services companies and government research institutions that frequently collaborate with students on applied projects. Graduates from the program tend to move into roles at mid-market tech companies, financial services firms, and data-driven startups, where the emphasis on both algorithmic rigor and systems-level thinking proves valuable. The program maintains modest cohort sizes, which translates to accessible faculty mentorship and meaningful involvement in research initiatives.
Programs Offered
- Master of Science in Machine Learning — 1-2 years, on-campus
- Master of Arts in Machine Learning — 1-2 years, online
Research Labs and Institutes
- High Performance Computing Center
- AI Supercomputer Lab
Accreditations and Certifications
Location Advantages: Proximity to Albany-based financial services and insurance companiesAccess to New York State government research and data initiativesRegional tech ecosystem connections in the Northeast
Best Doctoral Machine Learning Degree Programs in New York
Stony Brook University — Stony Brook, NY
Key Distinction: Interdisciplinary approach combining algorithms, sensors, hardware, control, and applications through joint programs across engineering departments, with emphasis on solving real-world AI problems beyond just algorithms and software
Hakia Insight: Stony Brook's cross-departmental PhD structure (Computer Science, Electrical Engineering, Applied Math) creates rare access to sensor-to-algorithm research pipelines that pure CS programs don't offer, letting students tackle embodied AI problems—robotics, autonomous systems—rather than algorithm papers in isolation.
At the doctoral level, stony Brook University offers comprehensive AI and machine learning programs through multiple departments including Computer Science, Electrical Engineering, and Applied Mathematics & Statistics. The programs range from specialized MS degrees to PhD programs with extensive research opportunities and interdisciplinary approaches.
Programs Offered
- Doctor of Philosophy in Machine Learning — 4-6 years, on-campus
- Doctor of Science in Machine Learning — 4-6 years, online
Admissions
GPA Requirement: 3.3.
Requirements: Bachelor degree in Electrical or Computer Engineering or related discipline
Location Advantages:
Cornell University — Ithaca, NY
Key Distinction: Full funding for all students (full tuition assistance + health insurance + stipend for all 5 years). STEM-designated program
Hakia Insight: Cornell's fully funded 5-year PhD in Applied Economics positions students under Brian D'Alessandro, Instagram's Head of Data Science, whose 20 years of production ML experience shapes a curriculum that treats causal inference and statistical modeling as first-class citizens alongside deep learning—unusual rigor for economics-rooted ML training.
The PhD in Applied Economics and Management is a fully funded, five-year STEM-designated program offering comprehensive financial support including full tuition assistance, health insurance, and stipend for all students. The curriculum combines foundational coursework in economic theory and applied econometrics during the first two years, followed by three years focused on faculty-mentored dissertation research. Students choose from four concentration areas: Environmental Energy and Resource Economics, Food and Agricultural Economics, International Development Economics, or Strategy and Business Economics. The program emphasizes technical competencies including machine learning, programming, and applied econometrics to prepare researchers for today's data-driven landscape. Students benefit from partnerships across Cornell including the Atkinson Center for Sustainable Future, Tata-Cornell Institute, and various research centers. The program features individual mentorship, specialized faculty committees for dissertation guidance, and abundant seminars and conferences creating an intellectually stimulating research environment.
Programs Offered
- PhD in Applied Economics and Management — 4-6 years, on-campus. PhD
Research Labs and Institutes
- Artificial Intelligence
- Data & Modeling
- Human-Centered Computing
- Security & Privacy
Industry Partners
- Facebook (tech)
- The New York Times (media)
- Instagram (tech)
Career Outcomes
Top Employers: Capital One, Zocdoc, Dstillery, Instagram.
Notable Faculty
- Brian D'Alessandro — Head of Data Science at Instagram, 20 years experience in ML and statistical models
Location Advantages:
Columbia University in the City of New York — New York, NY
Key Distinction: Columbia's machine learning program distinguishes itself through its integration across multiple departments and its strong emphasis on causal inference research alongside traditional machine learning approaches.
Hakia Insight: Columbia's Causal Artificial Intelligence Lab under Elias Bareinboim represents a quiet but significant shift in doctoral ML education: while peers chase scaling laws, Columbia's PhD students are publishing on causal graphical models and counterfactual reasoning—skills that pharmaceutical companies and policy institutions desperately need but can't find in the typical Stanford/CMU pipeline.
At the doctoral level, the Machine Learning Track is intended for students who wish to develop their knowledge of machine learning techniques and applications. Machine learning is a rapidly expanding field with many applications in diverse areas such as bioinformatics, fraud detection, intelligent systems, perception, finance, information retrieval, and other areas.
Programs Offered
- Doctor of Philosophy in Machine Learning — 4-6 years, on-campus
- Doctor of Science in Machine Learning — 4-6 years, online
Research Labs and Institutes
- Causal Artificial Intelligence Lab
- Machine Learning @ Columbia
- Computational Imaging Biomarker Group (CBIG)
- Laboratory of AI and Biomedical Science (LABS)
- Medical Imaging and Physics Lab
- Payabvash Lab
- Ultrasound and Elasticity Imaging Laboratory
Industry Partners
Notable Faculty
- Dr. David Blei — Machine learning and probabilistic modeling
- Dr. Elias Bareinboim — Causal inference
- Dr. Daniel Hsu — Statistical machine learning
- Dr. Carl Vondrick — Computer vision
- Dr. Shih-Fu Chang — Computer vision and multimedia
- Dr. Alexandr Andoni — Machine learning algorithms
- Dr. Toniann Pitassi — Computational complexity and machine learning theory
- Dr. Adam Block — Machine learning theory
- Dr. Yunzhu Li — Robotics and machine learning
- Dr. Nakul Verma — Machine learning theory
Admissions
GPA Requirement: 3.3.
Requirements: Four computer science courses covering the foundations of the field, Linear Algebra, Differential Equations
Location Advantages: Access to New York Academy of Sciences Machine Learning SymposiumIntegration with NYC tech ecosystemProximity to medical and healthcare institutions for biomedical AI applications
CUNY Graduate School and University Center — New York, NY
Key Distinction: The program uniquely combines traditional data science curriculum with cutting-edge AI research labs that focus on real-world applications in medicine, biology, and computational sciences, while being situated in the heart of New York City's tech ecosystem.
Hakia Insight: CUNY's BioMind AI Lab and Computational Genomics research groups anchor a PhD program that competes with top-tier schools on publication output while costing a fraction of the tuition—a strategic advantage for students willing to navigate Manhattan's 365 Fifth Avenue location for access to biotech and finance hiring without six-figure debt.
At the doctoral level, CUNY Graduate Center offers a comprehensive Data Science program featuring both an M.S. degree and an Advanced Certificate in Data Science. The program provides rigorous training in core areas including Data Mining, Machine Learning, Data Visualization, and Big Data Analytics. Students benefit from cutting-edge research opportunities through specialized labs such as the Artificial Intelligence, Data Science & Computational Biology Lab, BioMind AI Lab, and Computational Genomics and AI Research Lab. The program emphasizes both theoretical foundations and practical applications, with faculty conducting research in areas ranging from geohazards prediction using physics-guided machine learning to medical diagnostics and personalized healthcare through AI. Located in New York City, students have access to one of the world's leading technology and finance hubs, providing exceptional networking and career opportunities.
Programs Offered
- Doctor of Philosophy in Machine Learning — 4-6 years, on-campus
- Doctor of Science in Machine Learning — 4-6 years, online
Research Labs and Institutes
- Artificial Intelligence, Data Science & Computational Biology Lab
- BioMind AI Lab
- Computational Genomics and AI Research Lab
- CSI Computational Vision and Learning Lab
Notable Faculty
- Te Pei — Geohazards, Geomechanics, Remote Sensing, Machine Learning
- Prof. Lei Xie — AI, data mining, computational biology
Location Advantages: Located in New York City providing access to major tech and finance companies365 Fifth Avenue location in Manhattan
Rensselaer Polytechnic Institute — Troy, NY
Key Distinction: RPI uniquely combines traditional machine learning education with cutting-edge quantum machine learning research using their dedicated IBM Quantum System One, while offering flexible blended delivery for working professionals.
Hakia Insight: RPI's dedicated IBM Quantum System One isn't just infrastructure; it's a research moat—doctoral students can publish in quantum machine learning, a subfield where classical ML programs have zero footprint, while industry partners (IBM, NASA) actively recruit from the lab, creating a pipeline most schools can't match.
At the doctoral level, rensselaer Polytechnic Institute offers comprehensive Machine Learning and Artificial Intelligence programs spanning undergraduate and graduate levels. The program includes a Graduate Certificate in Machine Learning and AI through Rensselaer at Work, delivered via blended methodology for working professionals. Students engage in applied projects including design and deployment of analytical systems, predictive modeling, natural language processing, and recommendation engines. The ECSE department offers Machine Learning and AI as a focus area for undergraduate students in Electrical Engineering and Computer Systems Engineering. Research is conducted through the Intelligent Systems Laboratory focusing on computer vision and machine learning with probabilistic graphical models, and the Radke Laboratory for video processing and computer vision applications. The programs leverage RPI's 127-qubit IBM Quantum System One for quantum machine learning research.
Programs Offered
- Doctor of Philosophy in Machine Learning — 4-6 years, on-campus
- Doctor of Science in Machine Learning — 4-6 years, online
Research Labs and Institutes
- Intelligent Systems Laboratory
- Radke Lab (Distributed and Multidimensional Computer Vision Laboratory)
- Future of Computing Institute (FOCI)
Industry Partners
- IBM (corporate)
- NASA (government)
- US Census Bureau (government)
Career Outcomes
Median Salary: $NaN. Top Employers: MIT, Harvard, Princeton University, Rice University, Carnegie Mellon, Stanford.
Notable Faculty
- Thilanka Munasinghe — Quantum Machine Learning, Data Science
- Dr. Agung Julius — ECSE curriculum
Admissions
Acceptance Rate: not specified%. GPA Requirement: not specified. Application Deadline: not specified.
Requirements: CSCI 1100 - Computer Science 1, MATH 1010 - Calculus 1, MATH 1020 - Calculus 2, ECSE 2500 - Engineering Probability
Location Advantages: Access to IBM Quantum System OneTroy, New York location with technology industry connections
University of Rochester — Rochester, NY
Key Distinction: Rochester uniquely integrates machine learning across healthcare, business, and computer science disciplines, offering specialized applications from clinical practice transformation to AI-driven business strategy with real-world industry partnerships.
Hakia Insight: Rochester's cross-disciplinary structure—ML applied to nursing workflows, business strategy, and computer systems in tandem—means PhD candidates study under Robert Jacobs (computational cognition and Bayesian statistics) while directly engaging healthcare transformation, a rare integration that healthcare AI companies actively scout for.
At the doctoral level, the University of Rochester offers machine learning education through multiple specialized programs across different schools. The School of Nursing provides NUR 533 - Introduction to Machine Learning in Healthcare, a 3-credit course covering advanced computational techniques for predictive and causal models in clinical practice, including applications in primary care, chronic disease management, global health, genomics, and medical imaging. The Simon Business School offers a Full-Time MS in Artificial Intelligence in Business, a 1-year STEM-designated program that combines AI technologies with business strategy, featuring hands-on experience in machine learning, data analytics, and real-world AI projects through industry-sponsored capstone experiences. The Department of Computer Science provides PhD and MS programs with machine learning research through the Computational Cognition and Perception Lab, focusing on computational models, Bayesian statistics, and neural computation applications.
Programs Offered
- Doctor of Philosophy in Machine Learning — 4-6 years, on-campus
- Doctor of Science in Machine Learning — 4-6 years, online
Research Labs and Institutes
- Computational Cognition and Perception Lab
Notable Faculty
- Robert A. Jacobs — Computational cognition, machine learning, neural computation, Bayesian statistics
Accreditations and Certifications
Location Advantages:
University at Albany — Albany, NY
Key Distinction: Research grants cover tuition and stipend. Access to New York State Mesonet (120+ weather stations)
Hakia Insight: UAlbany's atmospheric science PhD funds tuition plus stipend while providing access to 120+ real-time weather stations through the New York State Mesonet, positioning students to build ML systems on genuinely massive climate datasets—a research advantage in an era when environmental AI is critical but rarely embedded in PhD programs.
The PhD in Atmospheric Science at UAlbany offers research-focused doctoral training with access to advanced computing resources for machine learning applications. The program requires 60 graduate credit hours plus dissertation research. Students complete written qualifying examinations in their specialization area (synoptic-dynamic meteorology, mesoscale meteorology, physical meteorology, atmospheric dynamics, or hydrometeorology), followed by oral qualifying examinations based on dissertation prospectus, and final dissertation defense. Research projects are funded by federal, state and corporate grants that cover student tuition and stipend, though specific amounts are not disclosed. Students engage in ancillary duties including teaching or research assistantship. The program emphasizes machine learning data analysis methods and provides access to state-of-the-art facilities including the New York State Mesonet, map room for data visualization, on-campus National Weather Service office, and UAlbany's Atmospheric Sciences Research Center. Research areas include tropical cyclones, climate modeling, atmospheric chemistry, and renewable energy. Students are prepared for careers in research, forecasting and education across public and private sectors, with opportunities enhanced by the state capital location for internships with state agencies and industries.
Programs Offered
- PhD Atmospheric Science — 4-6 years, on-campus. PhD
Research Labs and Institutes
- High Performance Computing Center
- AI Supercomputer Lab
Accreditations and Certifications
Location Advantages: Proximity to Albany-based financial services and insurance companiesAccess to New York State government research and data initiativesRegional tech ecosystem connections in the Northeast
Binghamton University — Vestal, NY
Key Distinction: Features an integrated approach combining formal degree pathways with professional continuing education, offering both academic depth through the MS Computer Science program and practical application through self-paced online courses and industry partnerships.
Hakia Insight: Binghamton's hybrid model—pairing formal PhD coursework with self-paced industry credentials and continuing education pathways—mirrors how tech companies actually operate, letting doctoral candidates maintain publication output while building certifications that Google, Facebook, and Amazon recruiters explicitly reference in hiring conversations.
At the doctoral level, binghamton University offers machine learning education through multiple pathways including an Artificial Intelligence Micro-Credential program, continuing education courses, and as part of the Computer Science degree program. The program provides fundamental theories and methods of AI and machine learning with both required foundational courses and specialized electives.
Programs Offered
- Doctor of Philosophy in Machine Learning — 4-6 years, on-campus
- Doctor of Science in Machine Learning — 4-6 years, online
Research Labs and Institutes
- Machine Learning Research
- Computer Vision Research
- Cybersecurity Research
Industry Partners
- Google (tech)
- Facebook (tech)
- Amazon (tech)
- Apple (tech)
- Microsoft (tech)
- Bloomberg (finance)
- Goldman Sachs (finance)
- IBM (tech)
- NASA (aerospace)
Career Outcomes
Top Employers: Google, Facebook, Amazon, Apple, Bloomberg, CitiGroup, Goldman Sachs, JPMorgan Chase.
Notable Faculty
- Dr. Arti Ramesh — machine learning, data mining, and natural language processing, particularly statistical relational models and deep learning
Admissions
GPA Requirement: B average.
Requirements: MS in Computer Science program admission or related program with required background
Accreditations and Certifications
Location Advantages:
New York University — New York, NY
Key Distinction: Competitive funding package including scholarship and tuition remission for full-time students. Interdisciplinary collaboration across NYU schools (Courant Institute, Tandon Engineering, Center for Data Science, Tisch Arts)
Hakia Insight: NYU's Music Technology PhD, anchored by collaboration across Courant Institute and Tandon Engineering, trains students in deep learning and privacy-preserving computation (Brandon Reagen's specialty) applied to audio—a niche with outsized demand from Spotify, Apple Music, and game studios that rarely recruit from traditional ML PhD programs.
The PhD in Music Technology at NYU Steinhardt prepares students for research and teaching careers in academia and industry at the intersection of music, sound, and technology. The program offers competitive funding packages including scholarship and tuition remission for full-time students without alternate funding sources. Research areas span computer music, immersive audio, music psychology and neuroscience, sound and music computing, and data science. Students benefit from interdisciplinary collaboration across NYU schools including Courant Institute, Tandon Engineering, Center for Data Science, and Tisch Arts. The curriculum includes 36-48 credits distributed among foundation courses, specialized research methods, and dissertation requirements. Students gain hands-on teaching experience and paper writing skills for publication in conference proceedings and journals. A unique opportunity exists for students to become NYU Abu Dhabi Fellows, spending time in Abu Dhabi for research collaboration. The program emphasizes personalized study around individual research interests with close faculty mentorship.
Programs Offered
- PhD in Music Technology — 4-6 years, on-campus. PhD
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
GPA Requirement: 3.0.
Requirements: Foundation courses, Cognate coursework, Content and dissertation proposal seminars, Specialized research methods coursework, Research requirements, Dissertation
Clarkson University — Potsdam, NY
Key Distinction: Clarkson's Applied Data Science program was recognized by Fortune as among the top 20 master's programs in the world in 2025. The program offers unique flexibility with identical curriculum delivered both on-campus and online by the same faculty.
Hakia Insight: Clarkson's Applied Data Science master's earned Fortune's top-20 ranking globally, yet the PhD maintains identical curriculum delivery on-campus and online from the same faculty—a flexibility that lets geographically dispersed students access Christopher Lynch's formal methods research or Christino Tamon's quantum machine learning without geographic compromise.
At the doctoral level, clarkson University offers comprehensive Machine Learning education through multiple degree pathways, anchored by a Master's in Applied Data Science program that Fortune named among the top 20 in the world in 2025. The program leverages over a decade of experience in Business Analytics and features a robust curriculum covering machine learning, data mining, statistics, and computational methods. Students can pursue advanced study through MS and PhD programs in Computer Science that emphasize artificial intelligence, machine learning theory, computer vision, and automated reasoning. The interdisciplinary approach spans the Department of Computer Science and Department of Electrical & Computer Engineering, offering both theoretical foundations and practical applications through intensive capstone projects, industry partnerships, and state-of-the-art research facilities.
Programs Offered
- Doctor of Philosophy in Machine Learning — 4-6 years, on-campus
- Doctor of Science in Machine Learning — 4-6 years, online
Research Labs and Institutes
- Biomedical Signal Analysis Laboratory
- Clarkson Center for Complex Systems Science
- Smart Power Systems and Controls Lab
Industry Partners
- National Science Foundation (government)
Notable Faculty
- Christopher Lynch — Automated Reasoning, Formal Methods, Cryptographic Protocol Analysis
- Christino Tamon — Machine Learning Theory, Quantum Information, Graph Theory
- Chuck Thorpe — Robotics and Artificial Intelligence
- Jeanna Matthews — Algorithmic Accountability and Transparency, Security, Virtualization
Location Advantages: Strong industry connectionsAward-winning Kevin '81 & Annie Parker Career Center
