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Top Universities to Pursue a Ph.D. with a Focus Area in Machine Learning

Careers, Machine Learning, Education

Best PhD Programs in Machine Learning (ML) for 2020

These are the best universities to pursue a Ph.D. in machine learning

Stacy S.
Stacy S.
Apr 20, 2019 · 5 min read

Last updated on August 14, 2020

Considering various factors such as the research areas, research focus, courses offered, duration of the program, location of the university, honors, awards, and job prospects, we came up with the best universities to help you in your choosing process. This article is most suited for individuals who’d like to pursue a Ph.D. with a focus on machine learning and need some guidance on their decision making.

Feel free to jump to the end if you are looking for only the names of the Universities.

Note: The universities mentioned below are in no particular order.

Program Name: Ph.D. in Machine Learning
Research Ranking in Machine Learning: 1
Research Ranking in AI: 1
Duration: 4–5+ years
Location: Pittsburgh, Pennsylvania
Core courses: Advanced machine learning, statistics, research, statistical machine learning, data analysis, artificial intelligence.
Tracks available: Ph.D. in Machine Learning, Ph.D. in Statistics and Machine Learning, Ph.D. in Machine Learning and Public Policy, Ph.D. in Neural Computation and Machine Learning, Ph.D. in Computer Science, etc.
Focus areas: Machine learning, artificial intelligence, NLP, computer vision, robotics, deep learning, data mining, web and information retrieval, etc.
Further information: Contact the Machine Learning Department at CMU.

Program Name: Ph.D. in EECS
Research Ranking in Machine Learning: 2
Research Ranking in AI: 12
Duration: 5–6+ years
Location: Berkeley, California
Core courses: Computer architecture and logic design, computer science, high-level mathematics, electrical engineering basis, artificial intelligence.
Tracks available: Ph.D. in EECS.
Focus areas: Machine learning, artificial intelligence, NLP, computer vision, deep learning, data mining, web and information retrieval, etc.
Further information: Contact EECS at UC Berkeley.

Program Name: Ph.D. in Computer Science
Research Ranking in Machine Learning: 3
Research Ranking in AI: 3
Duration: 4–6+ years
Location: Stanford, California
Core courses: Mathematical and theory foundations, computer systems, applications, research, artificial intelligence.
Tracks available: PhD in Computer Science.
Focus areas: Machine learning, artificial intelligence, NLP, computer vision, deep learning, data mining, web and information retrieval, etc.
Further information: Contact Stanford Engineering.

Program Name: Ph.D. in EECS
Research Ranking in Machine Learning: 4
Research Ranking in AI: 5
Duration: 4–6+ years
Location: Cambridge, Massachusetts
Core courses: Computer architecture and logic design, computer science, high-level mathematics, electrical engineering basis, artificial intelligence.
Tracks available: PhD in Computer Science.
Focus areas: Machine learning, artificial intelligence, NLP, computer vision, deep learning, data mining, web and information retrieval, etc.
Further information: Contact MIT EECS.

Program Name: Ph.D. in Computer Science
Research Ranking in Machine Learning: 5
Research Ranking in AI: 2
Duration: 4–6+ years
Location: Ithaca, New York
Core courses: Mathematical and theory foundations, computer systems, applications, research, artificial intelligence.
Tracks available: PhD in Computer Science.
Focus areas: Machine learning, artificial intelligence, NLP, computer vision, deep learning, data mining, web and information retrieval, etc.
Further information: Contact Cornell Engineering.

Program Name: Ph.D. in Machine Learning
Research Ranking in Machine Learning: 6
Research Ranking in AI: 4
Course Duration: 4–6+ years
Location: Atlanta, Georgia
Core courses: Advanced machine learning, statistics, research, statistical machine learning, data analysis, artificial intelligence.
Tracks available: Ph.D. in Machine Learning, Ph.D. in Algorithms, Combinatorics, and Optimization, Ph.D. in Computer Science, Ph.D. in Computer Science and Engineering.
Focus areas: Machine learning, artificial intelligence, NLP, computer vision, deep learning, data mining, web and information retrieval, etc.
Further information: Contact Georgia Tech.

Program Name: Ph.D. in Computer Science
Research Ranking in Machine Learning: 7
Research Ranking in AI: 7
Duration: 5–6+ years
Location: Los Angeles, California
Core courses: Computer architecture and logic design, computer science, high-level mathematics, electrical engineering basis, artificial intelligence.
Tracks available: Ph.D. in EECS.
Focus areas: Machine learning, artificial intelligence, NLP, computer vision, deep learning, data mining, web and information retrieval, etc.
Further information: Contact UCLA.

Program Name: Ph.D. in Computer Science
Research Ranking in Machine Learning: 8
Research Ranking in AI: 16
Course Duration: 4–6+ years
Location: Austin, Texas
Core courses: Computer architecture and logic design, computer science, high-level mathematics, electrical engineering basis, artificial intelligence.
Tracks available: PhD in Computer Science.
Focus areas: Machine learning, artificial intelligence, NLP, computer vision, deep learning, data mining, web and information retrieval, etc.
Further information: Contact the University of Texas — Austin.

Program Name: Ph.D. in Computer Science
Research Ranking in Machine Learning: 10
Research Ranking in AI: 12
Duration: 4–6+ years
Location: New York City, New York
Core courses: Computer architecture and logic design, computer science, high-level mathematics, electrical engineering basis, artificial intelligence.
Tracks available: PhD in Computer Science.
Focus areas: Machine learning, artificial intelligence, NLP, computer vision, deep learning, data mining, web and information retrieval, etc.
Further information: Contact Columbia University.

Program Name: Ph.D. in Computer Science
Research Ranking in Machine Learning: 17
Research Ranking in AI: 47
Course Duration: 4–6+ years
Location: Princeton, New Jersey
Core courses: Computer architecture and logic design, computer science, high-level mathematics, electrical engineering basis, artificial intelligence.
Tracks available: PhD in Computer Science.
Focus areas: Machine learning, artificial intelligence, NLP, computer vision, deep learning, etc.
Further information: Contact Princeton.

To summarize, we have listed the top universities for a Ph.D. with a focus area in machine learning below:

  1. Carnegie Mellon University

2. University of California — Berkeley

3. Stanford University

4. Massachusetts Institute of Technology

5. Cornell University

6. Georgia Institute of Technology

7. The University of Texas at Austin

8. University of California — Los Angeles

9. Columbia University

10. Princeton University

If you see anything that may need to be revisited, please email me: sstanford@towardsai.net

US News & World Report, College Rankings, https://www.usnews.com/best-colleges

CSRankings: Computer Science Rankings, Machine Learning & Data Mining, http://csrankings.org/#/index?mlmining

CSRankings: Computer Science Rankings, Artificial Intelligence, http://csrankings.org/#/index?ai

US News & World Report, Best Graduate Schools, Top Science Schools, AI Rankings, https://www.usnews.com/best-graduate-schools/top-science-schools/computer-science-rankings

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Stacy S.

Written by

Stacy S.

Senior Editor at Towards AI | ✊🏿 #BlackinAI | For Authors @towards_ai → https://towardsai.net/contribute | Inquiries: sstanford@towardsai.net

Towards AI

Towards AI is a world’s leading multidisciplinary science publication. Towards AI publishes the best of tech, science, and engineering. Read by thought-leaders and decision-makers around the world.

Stacy S.

Written by

Stacy S.

Senior Editor at Towards AI | ✊🏿 #BlackinAI | For Authors @towards_ai → https://towardsai.net/contribute | Inquiries: sstanford@towardsai.net

Towards AI

Towards AI is a world’s leading multidisciplinary science publication. Towards AI publishes the best of tech, science, and engineering. Read by thought-leaders and decision-makers around the world.

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