8 Fully Funded Artificial Intelligence Master Programs in the US
University of Illinois Urbana-Champaign Programs Offered:MS in Computer Science Location:Thomas M. Siebel Center for Computer Science 201 N. Goodwin Avenue, MC-258 Urbana, IL 61801 Admission: Admission to the program is extremely competitive. Funding: Securing a fully funded offer to the program is extremely competitive.
The University of Illinois Urbana-Champaign offers a research-focused MS in Computer Science program.
It requires 32 credit hours of study, comprising 28 credit hours of coursework and a 4-credit thesis component. The program provides robust financial support opportunities, with many students receiving research or teaching assistantships that include both a stipend and full tuition coverage. According to student reports, these assistantships are readily available to qualified candidates in the department.
Students in the program can choose to study a good number of AI courses of high quality.
UIUC's Artificial Intelligence research group stands as one of the most distinguished AI research teams in academia, characterized by its diverse expertise and expanding scope. The group's research portfolio spans several key areas of artificial intelligence, including machine learning, computer vision, natural language processing, machine listening, and robotics.
In machine learning, faculty members focus on deep learning theory, reinforcement learning, and the development of novel algorithms for neural networks. They also address critical concerns in modern AI systems, such as scalability, security, and fairness. The computer vision team advances research in scene understanding, image-language integration, and innovative approaches to transfer learning. Natural language processing researchers concentrate on grounded language understanding and knowledge-driven text generation, while the machine listening faculty explores sound processing and speech recognition technologies.
The group's excellence is evidenced by numerous prestigious awards received by its faculty members, including multiple NSF CAREER awards, Sloan Research Fellowships, and IEEE/ACM Fellows appointments. Recent accomplishments include multiple best paper awards at major conferences and successful commercial ventures. Several faculty members have founded influential startups, such as Reconstruct and EarthSense, applying AI solutions to construction and agriculture respectively.
The AI group plays a pivotal role in two $20 million NSF-funded institutes: the AI Institute for Future Agricultural Resilience, Management, and Sustainability (AIFARMS) and the AI Institute for Molecular Discovery, Synthetic Strategy, and Manufacturing. These initiatives demonstrate the group's commitment to applying AI technologies to solve real-world challenges in agriculture and molecular science.
Cornell University Programs Offered:MS in Computer Science Location:402 Gates Hall, Cornell University, Ithaca, NY 14853 Admission: Admission to the program is extremely competitive. Funding: Securing a fully funded offer to the program is extremely competitive.
Cornell University's Master's program in Computer Science is an intimate and highly selective four-semester program that emphasizes advanced coursework, research, and teaching experience. The program maintains a small cohort of approximately 25-30 students total, admitting just 10-15 new students annually. This selective approach ensures personalized attention and maintains the program's high academic standards.
A distinguishing feature of this program is its teaching assistantship (TA) component. All enrolled students serve as full-time TAs throughout their four semesters, dedicating 15 hours weekly to teaching duties. In return, they receive comprehensive benefits including full tuition coverage, a living stipend, and health insurance. While additional summer opportunities for teaching, research, or instructorship positions may be available, they are not guaranteed. TA performance is crucial to maintaining good standing in the program, with evaluations conducted each semester.
Cornell's Computer Science department has established itself as a global leader in artificial intelligence since the 1990s, garnering numerous awards and recognition while maintaining a collaborative atmosphere that nurtures diverse research interests. The AI program encompasses several key areas:
The Machine Learning group exemplifies Cornell's interdisciplinary approach, bringing together over 30 faculty members and hundreds of students and alumni from various departments. The Natural Language Processing Group combines expertise from Computer Science, Information Science, and Linguistics departments across both the Ithaca and NYC Tech campuses, focusing on computational linguistics, language understanding systems, and applications in social sciences and humanities.
The robotics program (Robotics@Cornell) covers a comprehensive range of specializations, including autonomy, perception, control, and human-robot interaction. Research extends across various platforms, from aerial and home robots to autonomous vehicles and humanoid systems.
This program is particularly suited for self-motivated students with strong expository skills who thrive in research environments and enjoy undergraduate instruction. The combination of advanced study, research opportunities, and teaching experience provides a solid foundation for future academic or professional pursuits in computer science and artificial intelligence.
Princeton University. Programs Offered:Master of Science in Engineering (M.S.E.) and Master of Engineering (M.Eng.). in Computer Science Location:35 Olden Street, Princeton, New Jersey Admission: Admission to the program is extremely competitive. Funding: Securing a fully funded offer to the program is extremely competitive.
Princeton University offers two distinct graduate pathways in Computer Science: the Master of Science in Engineering (M.S.E.) and the Master of Engineering (M.Eng.). Both programs feature extensive coursework in AI (Artificial Intelligence) and provide exceptional financial support. Graduate students receive comprehensive funding packages that include full tuition coverage and competitive stipends, with teaching assistantships being the primary funding mechanism for master's candidates.
The university's artificial intelligence research portfolio encompasses four major domains: Machine Learning, Natural Language Processing, Robotics, and Vision & Graphics. Each area represents a cutting-edge approach to advancing computational capabilities and human-machine interaction.
In the machine learning domain, Princeton researchers are pushing beyond traditional programmed instructions to develop adaptive, intelligent systems. Their work spans multiple frontiers, including innovative deep learning architectures for various applications, advanced reinforcement learning methodologies, and theoretical investigations into deep learning foundations. Particular emphasis is placed on addressing algorithmic bias, developing sophisticated automatic differentiation techniques, and exploring connections with cognitive science and neuroscience.
The Natural Language Processing group focuses on enabling machines to comprehend and utilize human knowledge, particularly through language and text. Their research combines deep neural networks and reinforcement learning to create systems that can effectively process and respond to human communication, with applications across numerous real-world scenarios.
Princeton's robotics research aims to develop sophisticated systems that emulate human and animal capabilities. The program encompasses diverse areas such as perception, control, learning, and planning, with applications ranging from drone technology and autonomous vehicles to construction automation and soft robotics.
The Vision & Graphics research group explores the intersection of visual computing and physical world interaction. Their work encompasses computer optics, image rendering, computational fabrication, 3D printing, and the development of fair visual learning systems. The group also investigates novel approaches to visualizing computer-generated audio and music.
University of Georgia Programs Offered:MS in Artificial Intelligence Location:Institute for Artificial Intelligence Boyd GSRC, Room 516 University of Georgia Athens, GA 30602-7415 Admission: Admission to the program is highly competitive. Funding: Securing a fully funded offer to the program is extremely competitive.
The University of Georgia's (UGA) Institute for Artificial Intelligence (IAI) offers a Master of Science in Artificial Intelligence (MSAI) degree, representing a unique interdisciplinary approach to AI education. The program welcomes candidates from diverse academic backgrounds, emphasizing strong preparation in relevant fields such as psychology, philosophy, linguistics, computer science, logic, or engineering. Successful applicants demonstrate academic versatility and excellent communication skills in English.
The curriculum requires 30 graduate-level credit hours, including a master's thesis (3 hours). The core curriculum (11 hours) encompasses foundational courses in deductive systems, data mining or machine learning, artificial intelligence, and a faculty research seminar. Students must complete an additional 14 hours of specialized coursework, with 8 hours selected from technical AI courses (Group A) and 6 hours from interdisciplinary courses (Group B).
Group A offerings include advanced topics such as robotics, evolutionary computing, computer vision, and various machine learning applications. Group B provides a broader theoretical foundation through courses in linguistics, philosophy, psychology, and business ethics. Under special circumstances, students may fulfill select requirements through directed readings or specialized AI topics courses, subject to advisory committee approval.
The IAI's history reflects steady growth and evolution since its inception as a research group in 1984. Its transformation into the Artificial Intelligence Center in 1995 and subsequent elevation to institute status in 2008 demonstrate UGA's commitment to AI education and research. A recent restructuring in 2024 has positioned the institute for expanded cross-university collaboration and innovation.
The institute offers limited research assistantships, providing reduced tuition and monthly stipends in exchange for 13-15 hours of weekly project work. These positions are typically awarded annually, with decisions made in spring for the upcoming academic year.
The IAI maintains active research partnerships with various government agencies, private industry, and academic institutions, securing funding from organizations such as the National Science Foundation, Department of Energy, and Georgia Research Alliance. This collaborative environment enables faculty and students to engage in cutting-edge AI research and applications.
The College of William & Mary Programs Offered:M.S. Computer Science, Machine Learning Concentration Location:McGlothlin-Street Hall Room 126, 200 Stadium Dr, Williamsburg, VA 23185 Admission: Admission to the program is highly competitive. Funding: Securing a fully funded offer to the program is extremely competitive.
The College of William & Mary offers a Master of Science degree in Computer Science with a specialized concentration in Machine Learning, available in both thesis and non-thesis formats. The program structure varies based on the chosen path, with thesis-option students completing 30 credit hours (including 6 credits of thesis work) and non-thesis students fulfilling 32 credit hours of coursework.
The curriculum combines foundational computer science education with specialized machine learning training. All students must complete the core course in Analysis of Algorithms and at least two additional 600-level courses. The machine learning concentration requires successful completion of four specialized courses selected from a comprehensive portfolio, including Introduction to Machine Learning, Data Mining, Neural Networks for Machine Learning, Deep Learning, and Machine Learning Systems. Students pursuing the thesis option must focus their research on machine learning topics.
Financial assistance is primarily available through teaching assistantships, with research assistantships occasionally available through federal funding. First-year graduate students typically serve as teaching assistants, working approximately 20 hours per week in various capacities. These positions provide both monthly stipends and tuition coverage, though students remain responsible for living expenses and additional fees.
Teaching assistant responsibilities fall into three main categories: Unix/Linux network maintenance, laboratory instruction, and undergraduate course grading. Network maintenance positions require strong programming skills in C and Unix/Linux systems. Laboratory instruction roles, particularly for introductory and beginning programming courses, demand both subject expertise and effective communication skills.
The department actively supports students in securing additional funding opportunities, including automatically applying for specialized aid programs such as minority fellowships when students qualify. Assistantships may cover either the nine-month academic year or extend to a full twelve-month period, providing flexibility in financial support options.
Portland State University Programs Offered:MS in Computer Science with Track of Artificial Intelligence & Machine Learning. Location:1825 SW Broadway Portland, OR 97201 Admission: Admission to the program is more competitive. Funding: Securing a fully funded offer to the program is highly competitive.
Portland State University's Computer Science department provides advanced education in Artificial Intelligence and Machine Learning through its specialized MS track. This comprehensive program delves into the fundamental algorithms that power modern intelligent systems and learning technologies.
The curriculum encompasses a diverse range of subjects essential to AI and ML development. Students explore sophisticated concepts including knowledge representation, automated planning systems, logical reasoning frameworks, and advanced search methodologies. The program also covers cutting-edge applications in natural language processing, computer vision, and various machine learning paradigms, from statistical approaches to evolutionary and reinforcement learning techniques.
The track's core requirements include foundational courses in Artificial Intelligence (CS 541) and Machine Learning (CS 545). Students then select from an array of specialized courses, including advanced AI topics in combinatorial games and search, deep learning, statistical learning sequences, and ethical considerations in AI research. The program maintains partnerships with Oregon Health & Science University (OHSU), allowing students to access additional specialized courses in areas such as deep learning and natural language processing.
Financial support opportunities are available through teaching and research assistantships. Teaching assistantships offer monthly stipends and tuition remission in exchange for 15-20 hours of weekly work, which may involve teaching or grading under faculty supervision. Selection for these positions considers academic performance, references, and demonstrated teaching capability.
Research assistantships are awarded by individual faculty members based on students' potential contributions to specific research programs. These positions typically become available after students complete at least one term and demonstrate proficiency in relevant coursework. Doctoral candidates who have advanced to candidacy often receive research assistantships aligned with their dissertation work, potentially incorporating their assisted research into their thesis.
Saint Louis University Programs Offered:Artificial Intelligence, M.S. Location:One North Grand Boulevard St. Louis, MO 63103 Admission: Admission to the program is more competitive. Funding: Securing a fully funded offer to the program is highly competitive.
Saint Louis University (SLU) offers a comprehensive Master of Science program in Artificial Intelligence, designed to equip students with advanced knowledge in AI methodologies and their ethical implementation. The curriculum emphasizes both theoretical foundations and practical applications of AI and machine learning, culminating in either a research thesis or a team-based capstone project.
The program's interdisciplinary approach allows students to specialize in various domains through faculty partnerships across the university. Key application areas include autonomous systems, bioinformatics, data science, health outcomes, image processing, and natural language processing. The curriculum particularly emphasizes ethical considerations, addressing crucial topics such as societal impact, implicit bias in AI systems, and responsible technology deployment.
SLU's strategic location in Midtown St. Louis provides students with exceptional professional opportunities. The campus's proximity to the Cortex Innovation Community, a sprawling 200-acre technology district, offers valuable networking and collaboration possibilities. Students can participate in weekly Venture Cafe gatherings, connecting with technology professionals in an informal setting. Additionally, the nearby T-REX Technology Entrepreneur Center serves as a vibrant hub for tech startups and innovation.
The program benefits from strong ties to the local business community, including numerous Fortune 500 companies and emerging startups. Major employers actively recruiting computer science graduates include Boeing, Centene, Microsoft, Bayer, and World Wide Technologies, among others. Students can pursue summer internships, part-time work during their studies, and full-time positions upon graduation.
Financial support options are available through the computer science department, including merit-based tuition scholarships and graduate assistantships. These assistantships may cover full or partial tuition, health insurance, and living expenses in exchange for teaching or research contributions. Additionally, students can pursue external STEM scholarships from independent organizations.
East Tennessee State University Programs Offered:Master of Science in Computer Science with Concentration in Artificial Intelligence and Machine Learning Location:PO Box 70711 Johnson City, TN 37614 Admission: Admission to the program is competitive. Funding: Securing a fully funded offer to the program is more competitive.
East Tennessee State University (ETSU) offers a Master of Science in Computer Science with a specialized concentration in Artificial Intelligence and Machine Learning. This focused program emphasizes computational theory and algorithm design through a carefully structured curriculum of advanced courses. The core coursework includes Natural Language Processing and Text Analysis, Artificial Intelligence, Machine Learning, and Analysis of Algorithms.
The Department of Computing provides substantial financial support opportunities for full-time graduate students through two primary mechanisms: graduate assistantships (GAships) and tuition scholarships (TSships). Graduate assistants receive a competitive salary of $5,800 per semester, and both GA and TS positions include full tuition coverage for the duration of the appointment.
To maintain these positions, students must meet specific requirements. They must enroll and maintain full-time graduate student status throughout each semester of their appointment. Additionally, students must maintain a minimum 3.0 GPA and perform their assigned duties satisfactorily. Teaching assistants must enroll in CSCI 5019-001 (supervised teaching), while research assistants must take CSCI 5029-001 (supervised research).
The majority of graduate assistants serve as teaching assistants for the introductory course CSCI 1100 (Using Information Technology). Additional opportunities exist for teaching assistance in lower-division computing classes and laboratory supervision. These positions provide valuable teaching experience while supporting undergraduate education.
The application process for financial support is streamlined with program admission. All full-time applicants are automatically considered for both GAships and TSships. While awards typically follow an annual cycle beginning in fall semester, spring semester positions frequently become available. The department begins awarding assistantships and scholarships for fall semester in mid-to-late April. For optimal consideration, prospective students should submit their applications by April 1 for fall admission or November 1 for spring admission.
Admission to the program is extremely competitive. 
Admission to the program is highly competitive.
Admission to the program is more competitive.
Admission to the program is competitive.