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EECE 503: Data-Driven Engineering

Electrical & Computer Engineer · 4 credits · Electrical&ComputerEngineering

This course studies data-driven tools for engineering, including modeling, predicting, classifying, and controlling complex systems. Topics include dimensionality reduction and transforms, such as singular value decomposition, principal component analysis, Fourier and wavelet transforms, sparsity and compressed sensing, machine learning and data analysis such as regression, clustering, and deep neural networks.

Offered in 2 of the 26 listed terms (Spring 2026 to Spring 2027).

Prerequisites

EECE 501 and EECE 502

Prerequisite tree

Each course's own prerequisites, down to the first courses in the chain.

From Banner's catalog for Spring 2027. Banner lists only the requisites it enforces, so check the catalog entry too.

Required by (0)

No course lists it as a prerequisite.

Syllabi and course websites

None listed yet.

Instructors

InstructorSectionsTerms
Ramasubramanian, Bhaskar4Spring 2026 to Spring 2027

Every offering in the listed terms (4 sections)

TermSecCRNTypeMeetsInstructorEnrolledDelivery
Spring 2027022697LectureMW 4:30pm-6:20pm · KB 213Ramasubramanian, Bhaskar0/21Face to Face Instruction
Spring 2027022698LectureMW 4:30pm-6:20pm · ONLINE SYNCRamasubramanian, Bhaskar0/15Distance Instr-OnLine
Spring 2026023334LectureMW 4:30pm-6:20pm · KB 213Ramasubramanian, Bhaskar9/15Face to Face Instruction
Spring 2026023336LectureMW 4:30pm-6:20pm · ONLINE SYNCRamasubramanian, Bhaskar1/15Distance Instr-OnLine