Machine Learning Engineering MSMLE

Major: Machine Learning Engineering
Degree Awarded: Master of Science in Machine Learning Engineering (MSMLE)
Calendar Type: Quarter
Minimum Required Credits: 45.0
Co-op Option: Available for full-time, on-campus master's-level students
Classification of Instructional Programs (CIP) code: 14.0903
Standard Occupational Classification (SOC) code: 15-1132

About the Program

The MS in Machine Learning is designed to provide a strong academic background in machine learning and prepare students for a career as a machine learning expert engineer or similar position. Using a curriculum based on core machine learning topics, aligned mathematical theory and signal processing, this graduate program provides a solid mathematical and theoretical understanding of how machine learning algorithms are designed, implemented and applied to practical problems. Students will gain the ability to implement machine learning systems using standard programming languages, software frameworks and systems both as an individual and as a member of a development team.

Students are also encouraged to engage in thesis research. The combined thesis and research cannot exceed 9.0 credits. The MS program is organized so that a student may complete the degree requirements in less than 2 years of full-time study or 2-3 years of part-time study.

Students within the Master of Science in Machine Learning Engineering are eligible to take part in the Graduate Co-op Program, which combines classroom coursework with a 6-month, full-time work experience. For more information, visit the Steinbright Career Development Center's website.

Additional Information

For more information about the MS in Machine Learning Engineering program, please visit the Department of Electrical and Computer Engineering website.

Admission Requirements

Applicants must satisfy general requirements for graduate admission including a minimum 3.0 GPA (on a 4.0 scale) for the last two years of undergraduate studies, as well as for any subsequent graduate work. Students will be required to hold a BS in electrical engineering, computer engineering, or computer science; or a bachelor’s degree in an aligned area (e.g. statistics, neuroscience, etc.) in addition to an appropriate technical background which will be reviewed during the admissions process.

Full-time applicants are encouraged to take the GRE exam. Students who do not hold a degree from a US institution must take the TOEFL or IELTS exam within two years of application submission.

Degree Requirements

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Thesis Option: A minimum of two terms of laboratory-based research that leads to a publicly defended MS thesis. Students will be advised by a faculty member, and when applicable, a representative of industry or government sponsor.

Non-thesis Option: In lieu of research and thesis, students will complete six additional credits of coursework from the Mathematical Theory, Applications, or Signal Processing area.

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Co-op is an option for this degree for full-time on-campus students. To prepare for the 6-month co-op experience, students will complete: COOP 500. The total credits required for this degree with the co-op experience is 46.0

Students not participating in the co-op experience will need 45.0 credits to graduate.

Sample Plan of Study

Thesis Option

Non-Thesis Option
 

Full Time With CO-OP