Modern Applied Statistics: Data Mining


Stanford School of Humanities and Sciences



Examine new techniques for predictive and descriptive learning using concepts that bridge gaps among statistics, computer science, and artificial intelligence. This course emphasizes the statistical application of these areas and integration with standard statistical methodology. The differentiation of predictive and descriptive learning will be examined from varying statistical perspectives.



Complete Data Mining and Analysis (Stanford Course:STATS202) or
Introduction to Statistical Learning (Stanford Course:STATS216) with a B+ or better

Topics include

  • Classification & regression models
  • Multivariate adaptive regression splines
  • Prototype & near-neighbor methods
  • Neural networks

Note on Course Availability

The course schedule is displayed for planning purposes – courses can be modified, changed, or cancelled. Course availability will be considered finalized on the first day of open enrollment. For quarterly enrollment dates, please refer to our graduate certificate homepage.

012 Spring 2018-19 Online

Enrollment Closed

Dates:April 2 - June 4, 2019
Days: Tue, Thu
Times:1:30 pm - 2:50 pm
Units: 2.00-3.00
Instructors: Jerome Friedman
Delivery Option:
For Credit $2,520.00-$3,780.00 ?


Enrollment Dates: February 10 to March 18, 2019

This course may not currently be available to learners in some states and territories.