Data Modeling

Harvard Extension School

CSCI E-106

Section 1

CRN 26017

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This course explores data modeling methodologies with the goal of understanding how to choose, apply, and interpret appropriate statistical designs and analyses for practical data problems. Topics covered include understanding the relationships in the data, theory and application of linear and non-linear regression models, model building steps, diagnostic of models, and remedial measures. Students can count one of the following three courses—CSCI E-106, STAT E-109, or STAT E-139 (offered previously)—toward a degree or certificate.

Instructor Info

Hakan Gogtas, PhD

Head of US Model Validation Group, Deutsche Bank


Meeting Info

M 5:30pm - 7:30pm (1/27 - 5/17)

Participation Option: Online Asynchronous or Online Synchronous

In online asynchronous courses, you are not required to attend class at a particular time. Instead you can complete the course work on your own schedule each week.

Deadlines

Last day to register: January 23, 2025

Additional Time Commitments

Optional sections to be arranged.

Prerequisites

Proficiency in R programming, introductory probability and statistics, multivariate calculus equivalent to MATH E-21a, and linear algebra equivalent to MATH E-21b.

Notes

This course meets via web conference. Students may attend at the scheduled meeting time or watch recorded sessions asynchronously. Recorded sessions are typically available within a few hours of the end of class and no later than the following business day.

Syllabus

All Sections of this Course

CRN Section # Participation Option(s) Instructor Section Status Meets Term Dates
15765 1 Online Asynchronous, Online Synchronous Hakan Gogtas Open Th 5:30pm - 7:30pm
Sep 3 to Dec 21
26017 1 Online Asynchronous, Online Synchronous Hakan Gogtas Open M 5:30pm - 7:30pm
Jan 27 to May 17