Top 10 AI graduate degree programs – CIO

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Artificial Intelligence (AI) is a fast-growing and evolving field, and data scientists with AI skills are in high demand. The field requires broad training involving principles of computer science, cognitive psychology, and engineering. If you want to grow your data scientist career and capitalize on the demand for the role, you might consider getting a graduate degree in AI.
U.S. News & World Report ranks the best AI graduate programs at computer science schools based on surveys sent to academic officials in fall 2021 and early 2022.
Here are the top 10 programs that made the list as having the best AI graduate programs in the US.
The Machine Learning Department at Carnegie Mellon University was founded in 2006 and grew out of the Center for Automated Learning and Discovery (CALD), itself created in 1997 as an interdisciplinary group of researchers with interests in statistics and machine learning. CALD drew from the Statistics Department and departments within the School of Computer Science, as well as faculty from philosophy, engineering, the business school, and biological science.
Carnegie Mellon says the department’s research strategy is to maintain a balance between research into the cure statistical-computational theory of machine learning and research inventing new algorithms and new problem formulations relevant to practical applications.
The Machine Learning Department offers both doctoral and master’s programs in machine learning, including:
The MIT Department of Electrical Engineering and Computer Science (EECS) is the largest academic department at MIT. A joint venture with the MIT Schwarzman College of Computing offers three overlapping sub-units in electrical engineering (EE), computer science (CS), and artificial intelligence and decision-making (AI+D).
MIT says AI+D’s research explores the foundations of machine learning and decision systems (AI, reinforcement learning, statistics, causal inference, systems, and control), the building blocks of embodied intelligence (computer vision, NLP, robotics), applications to real-world autonomous systems, life sciences, and the interface between data-driven decision-making and society.
The EECS Department graduate degree programs include:
Stanford University’s Computer Science Department is part of the School of Engineering. The Stanford AI Lab (SAIL) was founded in 1962 as a center of excellence for AI research, teaching, theory, and practice. In addition to its in-person programs, Stanford Online offers the Artificial Intelligence Graduate Program entirely online. The AI program focuses on the principles and technologies that underlie AI, including logic, knowledge representation, probabilistic models, and machine learning.
Stanford offers both PhDs and an MSCS with an AI specialization.
The University of California–Berkeley Department of Electrical Engineering and Computer Sciences focuses its foundational research in core areas of deep learning, knowledge representation, reasoning, learning, planning, decision-making, vision, robotics, speech, and NLP. There are also efforts to apply algorithmic advances to applied problems in a range of areas, including bioinformatics, networking and systems, search, and information retrieval. It is closely associated with the Berkeley Artificial Intelligence Research (BAIR) Lab.
Berkeley offers both PhDs and master’s programs.
Cornell Bowers CIS College of Computing and Information Science has been building out its AI group since the 1990s. In Dec. 2021, it launched a new initiative, a new Radical Collaboration, laid out by scholars across the university to advance its reputation as a leader in AI research, education, and ethics. The initiative expands faculty working in core areas and other domains affected by AI advances. Recent interdisciplinary collaborations across the Ithaca Campus, Cornell Tech, and Weill Cornell Medicine have applied AI to issues ranging from sustainable agriculture and urban design to cancer detection, improving autonomous vehicles, and parsing quantum matter.
Cornell offers a Master of Engineering in Computer Science program, as well as a Computer Science Master of Science program, and PhD program.
Georgia Tech College of Computing says AI and machine learning represent a large swath of its faculty and research interests, including constructing top-to-bottom and bottom-to-top models of human-level intelligence; building systems that can provide intelligent tutoring; creating adaptive and intelligent entertainment systems; making systems that understand their own behavior; and building autonomous agents that can adapt in dynamic environments.
Different groups within the school emphasize different areas of research. The core faculty comes from the School of Interactive Computing, but there are also machine learning faculty in the schools of Computer Science and Computational Science & Engineering.
Georgia Tech offers both master’s and doctoral programs, including a PhD in Machine Learning.
The University of Washington Paul G. Allen School of Computer Science & Engineering offers an AI group that studies the computational mechanisms underlying intelligent behavior. Research areas include machine learning, NLP, probabilistic reasoning, automated planning, machine reading, and intelligent user interfaces. It collaborates closely with the Allen Institute for Artificial Intelligence (AI2).
The University of Washington offers a combined bachelor of science (BS)/master of science (MS) program created with industry-bound students in mind, a full-time PhD program, a professional master’s program (a part-time, evening program), and a postdoctoral research program.
The University of Illinois–Urbana-Champaign Grainger College of Engineering focuses its AI and machine learning program on computer vision, machine listening, NLP, and machine learning. In computer vision, the AI group faculty are developing novel approaches for 2D and 3D scene understanding from still images and video, low-shot learning, and more. The machine listening faculty are working on sound and speech understanding, source separation, and applications in music and computing. The machine learning faculty are studying the theoretical foundations of deep and reinforcement learning; developing novel models and algorithms for deep neural networks, federated, and distributed learning; and studying issues related to scalability, security, privacy, and fairness of learning systems.
The university offers a CS PhD program, CS MS program, a professional master of computer science program, and a fifth-year master’s program.
The University of Michigan Computer Science and Engineering division offers an AI program comprised of multidisciplinary researchers studying rational decision making, distributed systems of multiple agents, machine learning, reinforcement learning, cognitive modeling, game theory, NLP, machine perception, healthcare computing, and robotics.
The university says research in the AI laboratory tends to be highly interdisciplinary, building on ideas from computer science, linguistics, psychology, economics, biology, controls, statistics, and philosophy.
The University of Michigan offers a PhD in CSE, master’s in CSE, and master’s in data science.
The University of Texas at Austin Department of Computer Science is focused on computer vision, evolutionary computation, machine learning, multimodality, NLP, neural networks, reinforcement learning, and robotics. It hosts myriad research centers and labs, including the Laboratory for Artificial Intelligence, which opened its doors in 1983 and investigates the central challenges of machine cognition, including machine learning, knowledge representation, and reasoning. Some others include the Institute for Foundations of Machine Learning, Machine Learning Lab, Machine Learning Research Group, and Neural Networks Research Group.
The University of Texas offers a PhD program, master’s program, online master’s program in computer science, online master’s program in data science, and five-year BS/MS programs.
Thor Olavsrud covers data analytics, business intelligence, and data science for CIO.com. He resides in New York.
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