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

(Fall 2017, 9 units)

Instructors: Sinan Aral, Erik Brynjolfsson

In this course, student teams select and deliver a project using analytics, machine learning, or other digital technologies to solve business problems.

Each project presents unique and specific challenges and includes access to a full dataset. Projects fit in a variety of industries and sectors and address a diversity of advanced problem types. In the first three years of the course, project sponsors included Amazon, Boston Public Schools, Dell Services, eBay, Gates Foundation, GE Transportation, IBM Watson, LinkedIn, MasterCard, Nasdaq, and others.

Class rosters from previous years have been comprised of students from a variety of programs including MBA, EMBA, Sloan Fellows, MFin, SDM, IDM, LGO, ORC, MSMS, EECS, and Urban Studies. Analytics Lab is also a required course for all students in the MBAn program.

Class meeting: Thursdays 4-5:30pm, plus a project sponsor pitch session in mid-September and a final presentation workshop in early December (attendance is mandatory).

Fall 2016 Syllabus

Application

The admissions cycle for Fall 2017 will begin in May. The link to the application will appear on this webpage.

Selective admission by application only (no bidding necessary): coursework or experience in analytics, statistics, computer science, management, and economics; 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 2016 Action Learning Open House.

Projects from 2014 and 2015 have included:

  1. Big Data as a Service (Amazon, 2014)

 
2. The “Myth of the Crystal Ball”: Understanding Forecasting Errors at Amazon (Amazon, 2015)

 
3. Understanding Supply and Demand in the Boston Public Schools (Boston Public Schools, 2015):

 
4. Populating "Popular Now": Rebooting our News Story Recommendation Algorithm (Christian Science Monitor, 2015):

 
5. Understanding Successful eBay Sale Prices (eBay, 2015):

 
6. Predicting Hospital Readmission (Dell, 2015)

 
7. Finding the Next Watson Use Case (IBM Watson, 2014)

 
8. Identifying Fraud for an Online Gift Card Platform (Raise Marketplace, 2015):

 
9. Predictive Maintenance in the Elevator and Escalator Industry (Schindler Elevator, 2015):

 
10. Using Geospatial Data to Develop a New Kind of Football Analytics (Telemetry Sports, 2015):

 
11. Multi-channel Consumer Profiling for eCommerce (WOOX Innovations, 2014)

 
12. Predicting New Product Adoption for American Apparel (Zensar, 2014)