Machine Learning Foundations

Machine learning (ML) is everywhere, and it's only becoming more embedded in the way we live, work, and make decisions. Think about some of the technologies you use every day, such as the ML-powered chatbots used by millions of people worldwide, like ChatGPT and Claude, or the recommendation systems that decide what shows up in your social media feed. All are practical applications of ML, a branch of artificial intelligence (AI) that allows computer programs to automatically improve through experience. Looking ahead, some of the world's most complex problems — such as accelerating drug discovery and diagnosing disease earlier than ever before — could depend on ML as a solution.

This "Machine Learning Foundations" summer course is taught by Cornell Tech's Visiting Lecturer Brian D'Alessandro and Ayham Boucher, Head of AI Innovation at Cornell, with content developed alongside Cornell University and Boston University faculty and industry leaders. In this nine-week, skills-based program, you will work with industry-relevant tools to analyze real-world datasets, identify patterns and relationships in data, and build ML solutions. By the end of the course, you will have hands-on experience working through the full ML life cycle to solve real-world problems.

Weekly synchronous lab sessions will give you the opportunity to explore these skills in a collaborative environment and gain hands-on experience in machine learning and data science. Ultimately, the foundational skills you acquire in this "Machine Learning Foundations" curriculum will prepare you to take on real-world industry challenges in Studio this fall.

During this part of the Break Through Tech AI Program, you can expect to spend about 12 to 15 hours per week on asynchronous online content and about three hours per week on synchronous lab sessions with other students.