15.572 - Analytics Lab: Action Learning Seminar on Analytics, Machine Learning & the Digital Economy

Instructors: Sinan Aral, Erik Brynjolfsson

In this seminar, student teams design and deliver a project based on the use of analytics, machine learning, large data sets, or other digital innovations to create or transform a business or other organization. The course is open by permission to MBAs, EMBAs, Sloan Fellows, and to students in other MIT programs with relevant coursework or experience in analytics, statistics, and information technology. A set of organizations, including sponsors of the MIT Initiative on the Digital Economy will offer projects for teams to work on, but students may also propose their own ideas and sites. The course culminates with presentations of final project results to an audience including experts, entrepreneurs and executives. Fall 2015, 9 units.

Class meeting: Tuesdays 4-5:30pm, plus a matching workshop on September 18, 4:00-8:00 and a final presentation workshop on December 8, 4:00-9:00.

Fall 2014 Syllabus

Applying

Applications for Fall 2015 are now closed.

Selective admission (no bidding necessary): Relevant coursework or experience in analytics, statistics, and information technology; course open by instructor permission only; applications considered on the basis of relevant learning, experience, and motivation toward data analytic work, with extra weight given to data analytic courses taken and to data analytic project and job experience; attention given to a representation of students with technical and computational experience, managerial experience, experience implementing analytical models, and entrepreneurial work using analytics.

The course is not open to listeners and in-person attendance is mandatory.

For questions, please contact Susan Young <susany @ mit.edu>; also see slides presented at April 2015 Action Learning Open House.

Projects from 2014 included:

1. Prime Share of Wallet (Amazon)

 
2. Big Data as a Service (Amazon)

 
3. Sales Projections for Chemco (Capgemini)

 
4. Finding the Next Watson Use Case (IBM Watson)

 
5. Multi-channel Consumer Profiling for eCommerce (WOOX Innovations)

 
6. Predicting New Product Adoption for American Apparel (Zensar)