Generative AI Lab

GenAI-Lab at a glance

  • Term

    Spring

  • Units

    9

  • Eligible students

    All MIT Sloan and MIT graduate students

  • Prerequisites

    No official prerequisite courses. 15.S68 recommended, at least one analytics or hands-on coding course encouraged for students wishing to participate in a project that involves leveraging the OpenAI, Claude, or Gemini APIs

     

  • Bid/Application

    Application

  • Host organization profile

    We accept a diverse range of hosts from large cap firms, startups (Series A or later), government, education, and nonprofits

  • Sample sectors

    Biopharma, cybersecurity, finance, government/nonprofit, healthcare, logistics, media, startups, tech, etc. 

  • Sample projects

    Projects can range from: 

    (1) developing AI prototypes with low-code / no-code tools

    (2) custom code written into a gen AI application by leveraging LLM APIs

    (3) writing strategy memos on the implications of generative AI developments, analyzing and assessing deployments of generative AI systems, developing AI usage policies for a marketplace business, value-chain analysis and investment memo for VC firm making AI investments 

The class

Students will work in teams to develop practical, low-code solutions and strategic roadmaps for sponsor companies. While coding skills are not required, students are expected to become proficient in using various low-code generative AI tools and platforms. The course will culminate in the creation and demonstration of a proof-of-concept or prototype that showcases the potential impact of generative AI for the host company.

By the end of this course, students will be well-prepared to lead generative AI initiatives, bridging the gap between technical capabilities and business strategy in this rapidly evolving field.

The primary criterion for projects is to provide a learning experience for the students. In addition, the projects should be of high relevance and interest to a particular organization and senior managers and professionals in it.

Project teams of three to four students are expected to work independently of regular class meetings. Host organizations will cover costs of travel and lodging, if any (as approved independently by the host organization). Each project team will have an MIT- associated faculty or research mentor to provide guidance and assistance and a link to outside project hosts on an as-needed basis.

Several optional skills-based sessions will be available during the semester, where students will have the opportunity to learn more about relevant analytic techniques and address issues they are confronting during the course of project work (details forthcoming). Attendance is strongly encouraged.

Required sessions

  • February 14, 2025

    Pitch Day

  • May 13, 2025

    Final presentations