Courses
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Descriptions
EECS 396, 496: Data Science Seminar

Quarter Offered

Spring : TuTh 3:30-4:50 ; Rogers

Prerequisites

213-level knowledge needed, will benefit from 339 (DB) and/or 343 (OS) background.

Description

In this seminar, we will survey the fundamentals of data science by reading state of the art research papers in this area. This class will cover the basics of how to manipulate, integrate, and analyze data at scale. To receive credit, students must give in-class presentations and complete a final project.

  • This course fulfills the CS Technical Elective requirement.

COURSE INSTRUCTOR: Prof. Jennie Rogers

Grading:

  • 40% - final project
  • 20% - class participation
  • 30% - in-class presentation
  • 10% - weekly write ups