ECE 537

Applied Data Analysis

Units: 1.5

Theory and application of modern data analysis and machine learning methodologies to larger scale real-world data analytics problems. Impacts of outliers, normalization processes, feature selection and extraction, data set biases, and noise on analysis quality. Implications of stationarity, ergodicity, and adversaries on data analysis processes. Students are required to complete a project.

Prerequisites:

  • One of ECE 485, ECE 535, ELEC 485, ELEC 535; or
  • permission of the department.

Graduate course in the Electrical and Computer Engineering program offered by the Faculty of Graduate Studies.

Schedules:
Summer 2019 Fall 2019 Spring 2020

Summer timetable available: February 15. Fall and Spring timetables available: May 15.

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