ECE 398 BD - Making Sense of Big Data

Official Description

Subject offerings of new and developing areas of knowledge in electrical and computer engineering intended to augment the existing curriculum. See Class Schedule or departmental course information for topics and prerequisites. Course Information: Approved for both letter and S/U grading. May be repeated in the same or separate terms if topics vary.

Section Description

Big Data is all around us. Petabytes of data is collected by Google and Facebook. 24 hours of video is uploaded on Youtube every minute. Making sense of all this data in the relevant context is a critical question. This course takes a holistic view towards understanding how this data is collected, represented and stored, retrieved and computed/analyzed upon to finally arrive at appropriate outcomes for the underlying context. The course is divided into three parts, with the first part focusing on foundations of machine learning, and the remaining two on specific application areas. Prerequisites: ECE 313 (or campus equivalent on basic undergrad probability) and some basic linear algebra. General mathematical maturity expected of engineering undergraduates. Target Audience: Juniors or Seniors

Subject Area

Core Curriculum

Course Director


Please note that this course has a related lab section. Students must also register for one of the following.

Title Rubric Section CRN Type Hours Times Days Location Instructor
Making Sense of Big Data ECE398 BB1 69003 LAB 0 1600 - 1650 W 2022 ECE Building
Making Sense of Big Data ECE398 BB2 69004 LAB 0 1700 - 1750 W 2022 ECE Building
Making Sense of Big Data ECE398 BB3 69005 LAB 0 1800 - 1850 W 2022 ECE Building

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