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Course Evaluation Results

Course Details

Spring 2015-2016
* SML 201 (QR)   No Pass/D/Fail

Introduction to Data Science

John D. Storey

This course provides an introduction to the burgeoning field of data science, which is primarily concerned with data-driven discovery and utilizing data as a research and technology development tool. We cover approaches and techniques for obtaining, organizing, exploring, and analyzing data, as well as creating tools based on data. Elements of statistics, machine learning, and statistical computing form the basis of the course content. We consider applications in the natural sciences, social sciences, and engineering.

Sample reading list:
See instructor for complete list

Reading/Writing assignments:
There will be four data analysis and/or programming projects due over the course of the semester. There will be primary and supplementary reading assigned by the instructor.

Paper in Lieu of Mid Term - 22%
Paper in lieu of Final - 22%
Quizzes - 12%
Problem set(s) - 44%

Other Requirements:
Statistical, design or other software use required

Prerequisites and Restrictions:
There are no official prerequisites for this course. However, it is recommended that students be comfortable with the basics of command-line computer usage and undergraduate-level mathematical notation and symbols (e.g., summation and product symbols, algebraic notation). Note: COS 126 or an equivalent course is NOT a prerequisite. Please see the course web site for further information..


Schedule/Classroom assignment:

Class numberSectionTimeDaysRoomEnrollmentStatus
43817 L01 11:00:00 am - 12:20:00 pm M W   Green Hall   0-S-6   Enrolled:59 Limit:60 Closed
43818 P01 10:00:00 am - 10:50:00 am Th   Lewis Library   121   Enrolled:36 Limit:36 Closed
43819 P02 03:30:00 pm - 04:20:00 pm Th   Lewis Library   121   Enrolled:23 Limit:35