Master's in Artificial Intelligence in United States
There are 10 master's Artificial Intelligence programmes for international students across 8 universities in United States. Tuition ranges from €21k to €52k. Browse the full list below, compare entry requirements, and explore scholarships to fund your studies.
AI and the Future of Cities
This course explores the profound impact of emerging technologies like artificial intelligence, automation, and digital infrastructure on the evolution of cities. You will delve into the economic and political forces driving urban technology, investigate the spatial and environmental consequences of data centers and AI systems, and examine the shifting dynamics between the public sector, private companies, and communities. The course also considers how technological disruptions are influencing public policy related to climate, energy, and infrastructure. Additionally, it addresses how AI adoption may reshape work, leisure, and daily life, and what these changes mean for real estate, public spaces, mobility, and local economic development. Learning will involve case studies, guest lectures, and group projects to analyze the potential influence of AI on the future form and function of urban environments.
Biostatistics in the Age of Artificial Intelligence
The Biostatistics in the Age of Artificial Intelligence program at the University of Michigan addresses the increasing intersection of statistical methods and advanced AI technologies within health and medicine. This program emphasizes that while AI is powerful for pattern recognition in large datasets, biostatisticians are crucial for ensuring its responsible and ethical application in healthcare. Students will learn to provide the necessary guardrails for AI, focusing on study design, causal inference, uncertainty quantification, and the ethical application of algorithms. The curriculum integrates traditional biostatistical methods with modern machine learning approaches, preparing graduates to tackle complex biomedical problems using tools like R and Python, and to work with high-dimensional data from genomics, imaging, and electronic health records. The program is situated within a university environment that is a leader in generative AI research and implementation, providing students with early access to secure AI tools and fostering a culture of responsible innovation.
Data Science, Analytics and Engineering (Bayesian Machine Learning), MS
The Master of Science in Data Science, Analytics and Engineering with a concentration in Bayesian machine learning is a collaborative program between the Ira A. Fulton Schools of Engineering and the School of Mathematical and Statistical Sciences at Arizona State University. This program is designed to equip students with the skills to transform complex data into accurate predictions using probabilistic frameworks. You will learn to apply Bayesian methods to extract meaningful insights from diverse, complex, and often uncertain datasets, an expertise highly valued across various industries. This concentration focuses on the statistical, probabilistic, and mathematical foundations of cutting-edge machine learning and data science. Students will explore hierarchical modeling, time series analysis, ensemble modeling, spatial modeling, and causal modeling, applying these tools in fields such as engineering, physics, biology, social sciences, economics, and finance. The program culminates in either a capstone project or a thesis, allowing students to conduct advanced Bayesian data analysis, modeling, and decision-making.
Human-AI Interaction
This course introduces students to the principles and practices of designing AI systems that are beneficial and useful to people. It explores key topics such as agency, ethics, bias, transparency, trust, and mixed-initiative systems. Students will learn to harness the power of AI to positively impact the human experience. The course emphasizes practical application through projects involving various AI domains like dialog systems, computer vision, recommender systems, and UI personalization. Assignments will primarily involve programming in Python and Javascript, with a focus on individual weekly mini-projects. While prior AI/machine learning experience is helpful, it is not a prerequisite. Students are expected to complete weekly readings and may be asked to present to the class. This course is suitable for both undergraduate and graduate students.
Human-Centered Artificial Intelligence (MA)
Lindenwood University's Master of Arts in Human-Centered Artificial Intelligence (AI) is a 30-credit graduate program designed for individuals from diverse academic and professional backgrounds. This program emphasizes the practical, real-world applications of AI, including content generation, image and video creation, and coding, rather than intensive mathematics or data science. It aims to empower non-specialists to leverage AI ethically and effectively, preparing them to lead in the rapidly evolving field of human-centered AI. No prior experience in AI, machine learning, or mathematics is required to enroll, as the curriculum focuses on developing these skills as needed based on individual career aspirations.
Master of Science in Applied Artificial Intelligence
Purdue University Northwest's Master of Science in Applied Artificial Intelligence equips students with a strong foundation in artificial intelligence and practical experience. This program focuses on implementing and applying AI techniques across various industries. Graduates will be prepared for roles in organizations that support the growth of AI-driven technologies, addressing the increasing demand for AI skills in the job market.
Master of Science in Artificial Intelligence (Online)
Maryville University offers an online Master of Science in Artificial Intelligence designed for individuals looking to advance their careers in this rapidly evolving field. The program focuses on the practical applications of AI and prepares students for the growing global demand in this sector. It leverages technology to deliver a flexible learning experience suitable for working professionals. The curriculum aims to equip students with the knowledge and skills necessary to understand, develop, and deploy AI solutions.
Master of Science in Computer Vision (MSCV)
The Master of Science in Computer Vision (MSCV) is a professional degree program designed to prepare students for careers in the industry, focusing on the field of computer vision. This full-time program spans 16 months, encompassing three academic semesters and one summer session. To graduate, students must successfully complete 111 units. The curriculum is structured with required core courses, flexible core options, and elective courses, allowing for a tailored learning experience in this rapidly evolving field.
Master of Science in Engineering Artificial Intelligence (MS EAI)
The Master of Science in Engineering Artificial Intelligence (MS EAI) at Carnegie Mellon University Africa is a 16-20 month (3-4 semesters) program designed to equip engineers with advanced skills to develop powerful solutions to complex challenges. This degree bridges artificial intelligence with specific engineering disciplines, addressing critical problems in areas like transportation, energy, agriculture, and healthcare. Students will gain a strong foundation in AI, machine learning, and data science, combining theoretical knowledge with practical, hands-on application to real-world scenarios. The program focuses on embedding AI within engineering frameworks, including representations, applications within engineered systems, and discipline-specific interpretations of system outcomes. You will learn to invent, tune, and specialize AI algorithms and tools specifically for engineering systems.
Online Master of Science in Software Engineering for Artificial Intelligence
The online Master of Science in Software Engineering for Artificial Intelligence at Boston University is designed for experienced and aspiring engineers to develop expertise in building and scaling production-grade software systems that integrate AI and large language models (LLMs). This program offers a rigorous blend of software engineering fundamentals, practical AI integration techniques, and human-centered system design, catering specifically to working professionals. Graduates will be equipped to create trustworthy, explainable, and usable AI-enabled applications. This program addresses the growing industry need for professionals who can bridge the disciplines of software engineering, data science, and AI. Unlike programs that teach these areas in isolation, this degree focuses on how to reliably, securely, and ethically deploy AI models in real-world systems. You will learn to manage AI-generated code, design scalable data pipelines and MLOps workflows, and build systems that are both intelligent and user-friendly, preparing you for advanced roles in AI software engineering. Offered by the Boston University College of Engineering, this fully online master's program delivers the same academic rigor as its on-campus counterparts, taught exclusively by BU Engineering faculty. The curriculum emphasizes hands-on application with industry-relevant tools and real-world datasets, culminating in a year-long capstone project. A foundational bootcamp ensures all students, regardless of their prior background, are prepared for the advanced coursework, making it an accessible yet challenging path to leading the future of AI-powered software.
Frequently asked questions
How many Artificial Intelligence programmes are there in United States?
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10 across 8 universities, listed on this page.
Can international students apply?
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Yes — these programmes admit international students; check each programme's entry requirements and language of instruction.