Curriculum

The Master of Science in Artificial Intelligence for Learning is a 30-to-36-credit graduate program designed for students who want to build and shape the future of learning. This interdisciplinary curriculum merges cognitive science, machine learning, and human-computer interaction, framing AI as a tool through which to drive equitable, evidence-based educational transformation. 

Core Course Sequence

The core sequence establishes a shared interdisciplinary vocabulary, seamlessly combining human cognition, machine capabilities, and user-centered design. Students have the opportunity to take additional elective courses across NYU (e.g., Courant Institute School of Mathematics, Computing, and Data Science, SPS Tisch, and Tandon School of Engineering).

Internships

The internship seminar is a 3-credit, semester-long elective course that provides students with professional field experience in diverse career areas. This opportunity will allow you to explore diverse opportunities in the profession throughout the New York metropolitan area, learning through supervised participation in instructional technology, instructional design and production, and a wide range of other professional positions and practices.

Internships are an essential complement to academic course work, particularly if you have not yet had professional work experience. Internships enable you to apply and refine what you learn in your coursework, under the supervision of professionals in a professional setting.

Culminating Experience

The program culminates in a year-long capstone experience that demonstrates students' ability to apply interdisciplinary skills in AI, learning science, and design to real-world educational challenges.

You'll be guided through the process of identifying and defining a meaningful education problem in collaboration with relevant stakeholders, conducting field research and systems analysis to engage in an iterative design process. Then, you'll implement the technical aspects of your proposed solution and refine your prototypes through multiple evaluation cycles. The sequence culminates in the development of a final project deliverable and a professional pitch presentation, showcasing their solution’s design, rationale, and potential impact.