Machine learning course projects at MIT are a rare chance to practice real research judgment under tight time and compute constraints—without the pressures of funding, publication, or product delivery. Drawing on experiences across MIT ML courses, this article explains how to choose project questions that maximize insight, learning, and scientific value rather than scale or raw performance.