Data Mining for Business

Harvard Extension School

CSCI E-96

Section 1

CRN 26599

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This course introduces non-mathematical business professionals to data science principles widely used in today's corporations. Quantitative methods affect many of today's interactions for business leaders, students, and consumers. Emphasis is placed on practical uses and case studies utilizing data to inform business decisions rather than theoretical or complex mathematics. Case study topics include understanding customer demand, marketing, new market forecasting, revenue projections, and data mining to improve decisions. Learning goals include quantitative business application, basic programming, algorithm development, and process workflow. The course highlights methods that business leaders and data scientists have found to be the most useful. It introduces the basic concepts of R for data mining. This course is for students who want an introduction to how data science improves business outcomes.

Instructor Info

Ted Kwartler, MBA

Managing Director, Responsible AI, Accenture


Meeting Info

M 8:10pm - 10:10pm (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 22, 2025

Additional Time Commitments

Optional labs to be arranged.

Prerequisites

Since this course utilizes R throughout the semester students should complete the 4-hour free online course Introduction to R at DataCamp.com found here: https://www.datacamp.com/courses/free-introduction-to-r.

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
15736 1 Online Asynchronous, Online Synchronous Edward Kwartler Open M 8:10pm - 10:10pm
Sep 2 to Dec 20
26599 1 Online Asynchronous, Online Synchronous Edward Kwartler Open M 8:10pm - 10:10pm
Jan 26 to May 16