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Analytics Lab

The MIT Analytics Lab (A-Lab) is the IDE's flagship educational offering. In this graduate seminar, student teams engage with project host companies to deliver a project using analytics, machine learning, and other methods of analysis to develop results that diagnose, enable, or uncover solutions to real business issues and opportunities.

A-Lab is a graduate level seminar course, spearheaded by the IDE and is part of MIT Sloan School of Management’s suite of Action Learning offerings. The course is led by IDE faculty Sinan Aral.

During its first eight years, A-Lab has attracted a total of 700 students from a dozen MIT programs to work on 180 projects spanning IoT, digital technology, platforms, finance, marketing, e-commerce, retail, manufacturing, medical supply chains, workplace safety, and global health.

Some projects are tightly focused on dilemmas organizations currently face, which requires students to quickly understand particular business circumstances and domains before performing their descriptive, predictive, or causal analysis. Other projects are more open-ended, and students must think entrepreneurially about how to bring new value to existing data and suggest frontiers for future business opportunity.

For Project Host Companies

Propose Projects for A-Lab

We invite organizations from all sectors to participate as A-Lab Project Hosts. We are looking for projects that fit in a variety of industries and sectors; address a diversity of problem types; require advanced depth of analysis; and have ensured availability of clean and rich data at the outset of the project. We also seek to closely match the students’ capabilities and variety of skills, experience, and interests.

If you are interested in hosting a project and submitting a proposal for the 2023-2024 academic year, please reach out to us at

Submit an A-Lab Proposal

Organizations are invited to propose projects and become project hosts.

Submit a Proposal

For Students

Apply to A-Lab

Admission for MIT students by application only; evaluation based on coursework and experience in analytics, statistics, computer science, management, and economics. No bidding necessary. Students should apply for the course as individuals; student-driven team formation will take place in September 2023.

The course includes an extended project pitch session and a final presentation event, in addition to normally scheduled class meetings. The course is not open to listeners and attendance at all sessions is mandatory.

Students: Apply to A-Lab

Student applications are due by July 17th.

Student Application

Past Projects