In this section, Prof. Georgia Perakis discusses the variety of student groups required to learn this material, and how the instructional goals for each group are slightly different.
We teach these materials to students in several different programs: MBA students, Executive MBAs (EMBAs), Sloan Fellows, and students in the Leaders for Global Operations (LGO) program. Even within the MBA program, students tend to come to the class with a range of backgrounds, which can be challenging. For example, some students are traders, which means they are already familiar with statistics. These students come to the class thinking it’s a statistics course and will be too easy for them. But this is not a course in statistics. This is a course that teaches them how statistics and optimization can make a difference in business. This is a very different focus than using statistics to do hypothesis testing. For other students, working with data and building models might be extremely difficult because they are coming from a completely different background and may have not have taken any statistics or optimization courses before coming to MIT.
We hope that later on, when [the MBAs] become managers, they will remember what we taught them and … will continually refresh their knowledge in this domain.
—Georgia Perakis
What we hope students learn differs slightly depending on their program. For students in the MBA program, there are tools relating to analytics, statistics, and optimization that are extremely useful. We want to teach them how these tools are valuable, and to give them a strong foundation for other classes. We also hope that later on, when they become managers, they will remember what we taught them and that they will continually refresh their knowledge in this domain. This is the goal for the MBAs.
EMBAs are executives already, and some of them have their own companies or are CEOs. Our goals for them are similar to our goals for MBA students, but because they are not going to become coders, we focus less on the technical aspects and focus more on high-level projects when presenting the materials. The EMBAs immediately apply what they’re learning in their business settings some even during the duration of the course. They understand that this is not a statistics or an optimization course. Our goal is to show them how they can change their businesses through data and models in order to make better decisions. Our approach is similar with the Sloan Fellows.
LGOs are required to take two courses in data and modeling. One course addresses probability and statistics and the other focuses on optimization. Their experience is more modular and a little more advanced. Because most of them they are engineers already, we try to make the course more technical, but overall, the material is similar to that presented in the other programs.