Data Science for Marketing

The Data Science for Marketing certificate introduces students to common statistical and machine learning procedures in order to make marketing decisions. In this course, participants will focus on generating and interpreting statistical and machine learning outputs for effective decision-making. Students will work with the Python open-source coding language to execute common data science procedures used in marketing, including correlation analysis, regression, analysis of variance, segmentation, forecasting, and conjoint analysis.

The certificate includes readings and case studies to apply principles of analytics to decision-making situations. Basic familiarity with the Python coding language, statistics, and marketing concepts is helpful for this course.

Upon successful completion of this certificate, participants will be able to:

• Generate and interpret statistical and machine learning outputs for effective decision-making
• Understand what data science outputs say about marketing strategy
• Work with the Python open-source coding language to execute common data science procedures used in marketing including correlation analysis, regression, analysis of variance, segmentation, forecasting, and conjoint analysis
• Use readings and cases to apply principles of analytics to decision-making situations

Daniel Zielaski serves as Vice President of Personalization & Growth at Salesforce where he and his team focus on building algorithms and personalizing content recommendations to increase the likelihood of a click, signup, purchase or completion of a key action. Prior to Salesforce, Daniel led marketing analytics and product data science for Mozilla and served the U.S. Federal Communications Commission as the Director of Data Strategy for the Universal Service Fund.

Details

Dates: March 21 – May 2
Schedule: Tuesdays 6–9 p.m.
Location: Online  
Instructor: Daniel Zielaski
Continuing Education Units: 2
Cost: $995 | $248.75 for USF students