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Best Masters Programs in Machine Learning (ML) for 2020
Careers   Editorial   Education   Machine Learning

Best Masters Programs in Machine Learning (ML) for 2020

Last Updated on January 6, 2022 by Editorial Team


Best Universities for a Masters Degree in Machine Learning
Top Universities to Pursue an MS with a Focus Area in MachineΒ Learning

Careers, Education, MachineΒ Learning

Best Masters Programs in Machine Learning (ML) forΒ 2020

These are the best universities to pursue a master’s degree in machineΒ learning

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 master’s degree 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.

1. Carnegie Mellon University

Program Name: Master of Science in Machine Learning
Research Ranking in Machine Learning: 1
Research Ranking in AI: 1
Duration: 1–2 years
Location: Pittsburgh, Pennsylvania
Core courses: Advanced machine learning, statistics, research, statistical machine learning, data analysis, artificial intelligence, data science.
Tracks available: Masters of Science in Machine Learning, Fifth Year Masters in Machine Learning, Secondary Masters of Science in Machine Learning, Masters of Computational Data Science, Master of Science in Computer Science.
Focus areas: Machine learning, artificial intelligence, NLP, computer vision, robotics, deep learning, data mining, web and information retrieval, computer science, etc.
Further information: Contact the Machine Learning Department at CMU.

2. University of Californiaβ€Šβ€”β€ŠBerkeley

Program Name: Masters in Data Science, Masters in EECS
Research Ranking in Machine Learning: 2
Research Ranking in AI: 15
Duration: 1–2.5+ years
Location: Berkeley, California
Core courses: Research design, data engineering, machine learning, data mining, ethics and privacy, data visualization, computer science, statistical analysis.
Tracks available: Masters in Data Science, Masters in EECS with a focus on machine learning.
Focus areas: Machine learning, artificial intelligence, NLP, computer vision, deep learning, data mining, web and information retrieval, etc.
Further information: Contact UC Berkeley.

3. Stanford University

Program Name: Masters of Science in Computer Science
Research Ranking in Machine Learning: 3
Research Ranking in AI: 3
Duration: 3–5+ years
Location: Stanford, California
Core courses: Mathematical and theory foundations, computer systems, applications, research, artificial intelligence.
Tracks available: Masters of Science in Computer Science with a focus on machine learning.
Focus areas: Computer science, Machine learning, artificial intelligence, NLP, computer vision, deep learning, data mining, web and information retrieval, etc.
Further information: Contact Stanford Engineering.

4. Massachusetts Institute of Technology

Program Name: Master of Science in EECS
Research Ranking in Machine Learning: 4
Research Ranking in AI: 5
Duration: 2–3+ years
Location: Cambridge, Massachusetts
Core courses: Computer architecture and logic design, computer science, high-level mathematics, electrical engineering basis, artificial intelligence.
Tracks available: Masters in EECS with a focus on machine learning.
Focus areas: Machine learning, artificial intelligence, NLP, computer vision, deep learning, data mining, web and information retrieval, etc.
Further information: Contact MIT EECS.

5. Cornell University

Program Name: Masters in Computer Science
Research Ranking in Machine Learning: 5
Research Ranking in AI: 2
Duration: 2–2.5+ years
Location: Ithaca, New York
Core courses: Mathematical and theory foundations, computer systems, applications, research, artificial intelligence.
Tracks available: Masters in Computer Science.
Focus areas: artificial intelligence, machine learning, computer science, programming languages and logic, scientific computing and applications, systems, theory, and computation.
Further information: Contact Cornell Engineering.

6. Georgia Institute of Technology

Program Name: Masters in Computer Science
Research Ranking in Machine Learning: 6
Research Ranking in AI: 13
Course Duration: 1–2+ years
Location: Atlanta, Georgia
Core courses: Advanced machine learning, statistics, research, statistical machine learning, data analysis, artificial intelligence.
Tracks available: Masters in Computer Science with a specialization in Machine Learning.
Focus areas: Machine learning, artificial intelligence, NLP, computer vision, deep learning, data mining, web and information retrieval, computer science, etc.
Further information: Contact Georgia Tech.

7. University of Washington

Program Name: Masters in Computer Science, Master of Science in Data Science.
Research Ranking in Machine Learning: 7
Research Ranking in AI: 6
Duration: 1–2.5+ years
Location: Seattle, Washington
Core courses: Computer architecture and logic design, computer science, high-level mathematics, electrical engineering basis, artificial intelligence, data science, machine learning, applied machine learning, statistical analysis.
Tracks available: Master of Computer Science, Master of Science in Data 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 Washington.

8. University of Californiaβ€Šβ€”β€ŠLos AngelesΒ (UCLA)

Program Name: Masters of Science in Computer Science
Research Ranking in Machine Learning: 8
Research Ranking in AI: 7
Duration: 2.5–3+ years
Location: Los Angeles, California
Core courses: Computer architecture and logic design, computer science, high-level mathematics, electrical engineering, artificial intelligence, machine learning.
Tracks available: Master of Science in Computer Science.
Focus areas: Machine learning, artificial intelligence, NLP, computer vision, deep learning, data mining, web and information retrieval, etc.
Further information: Contact UCLA.

9. University of Illinois at Urbana-Champaign (UIUC)

Program Name: Master of Science in Computer Science
Research Ranking in Machine Learning: 9
Research Ranking in AI: 4
Course Duration: 1.5–2.5+ years
Location: Champaign, Illinois
Core courses: Computer architecture and logic design, computer science, high-level mathematics, electrical engineering, artificial intelligence, machine learning.
Tracks available: Master of Science 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 UIUC.

10. Columbia University

Program Name: Master of Science in Computer Science
Research Ranking in Machine Learning: 10
Research Ranking in AI: 12
Duration: 1.5–3+ year
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: Master of Science in Computer Science.
Focus areas: Computational biology, computer security, foundations of computer science, machine learning, NLP, network systems, software systems, vision, graphics and robotics, artificial intelligence, theory.
Further information: Contact Columbia University.

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

  1. Carnegie Mellon University
  2. University of Californiaβ€Šβ€”β€ŠBerkeley
  3. Stanford University
  4. Massachusetts Institute of Technology
  5. Cornell University
  6. Georgia Institute of Technology
  7. University of Washington
  8. University of Californiaβ€Šβ€”β€ŠLos Angeles
  9. University of Illinois at Urbana-Champaign
  10. Columbia University

If you see anything that may need to be revisited, please email me: [email protected]


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