The goal for any MUSA collaboration is to augment the student’s existing domain expertise with skills to promote evidenced-based, data-driven decision making. In the modern labor market, these skills are as timely and important as ever.
The student armed with skills from Wharton and MUSA can work and manage across business development and engineering teams. They can think critically about the business process; motivate an algorithmic solution; manage the development, deploy the product and interpret results in the business context. For a traditional MUSA student, the skills are the same, but the business process is government-centric and considers multiple bottom lines including equity, politics and economics.
While a host of data science/analytics programs exist across the University and the nation, MUSA is unique in its ability to teach engineering solutions to social science students. Instead of leading with the inner workings of an algorithm, MUSA motivates a relevant use case and then introduces an algorithmic solution. This model works particularly well with MBA students who are well-versed in issues like economics, finance and risk aversion.
Master of Urban Spatial Analytics/MBA (2 years, 21 CUs)
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Year I: Wharton School MBA core (11.5 CUs)
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Year II: Urban Spatial Analytics (5 CUs) + Wharton School MBA major (4.5 CUs)