EMSE 6035: Marketing of Technology
Course Information:
Description:
This course provides students with a quantitative foundation for informing design decisions in an uncertain, competitive market. Over the course of the semester, students will apply theory and methods to a team project to assess the market competitiveness of a new product or emerging technology. Topics include consumer choice modeling, programming in R, survey design, conjoint analysis, optimization, market simulation, and professional communication skills. In addition to gaining a theoretical foundation in these topics, students will develop the skills, best practices, and design principles central to using data analytics to generate design insights. The course is geared towards learning how to analyze data in the R programming language, though no prior programming experience is required.
Prerequisites:
This course assumes working knowledge of multivariable calculus, linear algebra, basic regression, and probability theory.
Not sure whether you should sign up? Take this self-assessment quiz. It shouldn't take more than 10-20 minutes to complete, and you can check the solutions to see how you did. If you have trouble answering these questions, you may find the course challenging, and you may want to take other courses first or search for refresher courses / materials prior to taking EMSE 6035.
Learning Outcomes:
Having successfully completed this course, students will be able to do the following:
Recorded lectures:
This course provides students with a quantitative foundation for informing design decisions in an uncertain, competitive market. Over the course of the semester, students will apply theory and methods to a team project to assess the market competitiveness of a new product or emerging technology. Topics include consumer choice modeling, programming in R, survey design, conjoint analysis, optimization, market simulation, and professional communication skills. In addition to gaining a theoretical foundation in these topics, students will develop the skills, best practices, and design principles central to using data analytics to generate design insights. The course is geared towards learning how to analyze data in the R programming language, though no prior programming experience is required.
Prerequisites:
This course assumes working knowledge of multivariable calculus, linear algebra, basic regression, and probability theory.
Not sure whether you should sign up? Take this self-assessment quiz. It shouldn't take more than 10-20 minutes to complete, and you can check the solutions to see how you did. If you have trouble answering these questions, you may find the course challenging, and you may want to take other courses first or search for refresher courses / materials prior to taking EMSE 6035.
Learning Outcomes:
Having successfully completed this course, students will be able to do the following:
- Wrangle and summarize data in R.
- Build and estimate discrete choice models.
- Design effective surveys to obtain rich data.
- Analyze consumer choice data to understand consumer preferences.
- Design and create effective, reproducible charts and presentations.
- Communicate results in terms of design insights.
Recorded lectures: