Graduate Certificate Program in Engineering Machine Learning Systems

SUNY Stony Brook University

The Engineering Machine Learning Systems certificate program educates about the mathematical theory, fundamental algorithms, and optimized engineering of computational learning systems used in real-world, big data applications. Students will also study modern technologies used in devising such data systems, including software tools, architectures, and related hardware structures. Comprehensive, hands-on student projects on designing, implementing, and testing real-world learning systems are part of the certificate program. The certificate program includes a total of four courses: three required courses and one elective course.Certificate RequirementsTo receive the Stony Brook certificate in Engineering Machine Learning Systems, a student must be currently enrolled in an MS or PhD program in the Electrical and Computer Engineering Department and must complete four courses as specified below, with at least a B grade in each course.Foundations (1 required course)ESE 503 Stochastic SystemsFundamental Methods (2 required courses)ESE 588 Pattern RecognitionESE 589 Learning Systems for Engineering SystemsApplications (1 course out of four electives)ESE 568 Computer VisionESE 587 Hardware Architectures for Machine LearningESE 590 Practical Machine LearningBMI 511/ESE 569 Translational Bioinformatics