15.572 - Analytics Lab: Action Learning Seminar on Analytics, Machine Learning & the Digital Economy (Fall 2016, 9 units)

Instructors: Sinan Aral, Erik Brynjolfsson

In this seminar, student teams design and deliver a project using analytics, machine learning, large data sets, or other digital innovations to address a business or organizational opportunity or issue. The course is open by permission to MBA, EMBA, Sloan Fellows, and graduate students in other MIT programs with relevant coursework or experience in analytics, statistics, and information technology.

Each project proposal presents unique and specific challenges and provides access to a full dataset. Projects reflect a diversity of advanced issues and challenges. Teams are matched to projects at Match Day in mid-September and final presentations will occur in early December. Mentors are assigned to each team. In the first two years of the course, project sponsors included Amazon, Boston Public Schools, Dell Services, eBay, IBM Watson, MasterCard, Nasdaq, and others.

Class meeting: Thursdays 4-5:30pm, plus a matching workshop on September 16 and a final presentation workshop on December 12 (attendance is mandatory).

Fall 2015 Syllabus


Applications for Fall 2016 are now closed.

The admissions cycle for Fall 2017 will begin in May 2017.

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 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)