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Learn to harness the power of artificial intelligence to generate new content

Welcome to the Generative AI Summer Institute, where technology meets imagination! Our program is designed for high-school students passionate about technology, artificial intelligence, and creative expression. Over the course of three weeks, students will embark on a journey exploring the fascinating world of Generative AI.

Generative AI is an exciting area of artificial intelligence that focuses on machines’ ability to create something new, like generating story, art, music, or even entirely new ideas. Generative AI works by training a computer program on a vast amount of data. For example, if you want to create a generative AI that paints pictures, you would train it on thousands of existing paintings. The AI learns the patterns, styles, and techniques used in these paintings. Once trained, the AI can generate new paintings inspired by what it has learned. It’s like teaching the AI to recognize what makes a painting beautiful and then letting it create its own beautiful artwork based on that knowledge.

Fees and Payment Info

The program fee includes the unit fees for the UCLA coursework offered as part of the program and thus varies by UC student status. In addition to the program fee, students are assessed other campus and administrative fees during the summer. This is a summary of fees that commonly apply to the selected student type.

Actual tuition and fees are subject to change by the University of California. Visit the fees, payment, and financial aid section for important disclaimer, as well as more details on fees, payment instructions, and information on delinquency, refunds, and financial aid.


Program Fee
Registration Fee
Document Fee (for first-time Summer Sessions students)
Total Estimated Fees:
* Fees only apply for certain student types

Meet your instructors

Nanyun Peng

Assistant Professor

Nanyun (Violet) Peng is an Assistant Professor of Computer Science at the University of California, Los Angeles. She received her Ph.D. in Computer Science from Johns Hopkins University, Center for Language and Speech Processing. Her research focuses on generalizability of NLP technologies, with applications to creative language generation, low-resource information extraction, and zero-shot cross-lingual transfer. Her works have won the Outstanding Paper Award at NAACL 2022, the Best Paper Award at AAAI 2022 Deep Learning on Graphs workshop, and have been featured in the IJCAI 2022 early career spotlight. Her research has been supported by several DARPA, IARPA, NIH grants and several industrial research awards.