Your days begin with gathering on campus and signing in to your respective program tracks. From there, you head to your respective lab spaces for an opening circle to frame the day, including a quick social check-in and content-related invitation to learning. Each day, you get to engage in STEM-related explorations and investigations, sometimes in pairs and sometimes in small groups. You engage with a related guest lecturer, usually a UC Berkeley AI or Computer Science (CS) professor, describing their research on AI systems. After these lectures and Q&A with the professors, we continue in a participatory lecture. This lecture is broken into smaller pieces with individual and group tasks interspersed to provide opportunities to engage with the content from the lecture. These participatory lectures cover the basics of the pertinent AI concepts that are foundational to the project work aspects of the program. Midday, you take time to eat lunch on campus and enjoy some social downtime with peers in your track and other STEM tracks. Afternoons, you focus on either foundational technical skill development or project work. Specifically, earlier in the week, most afternoons are spent on introductory Python programming knowledge, hands-on experience developing machine-learning models, and building an understanding of mathematical concepts underlying AI systems. Later in the week, these skills and knowledge sets are applied to real-world AI problems under the mentorship of AI graduate students. You will also visit robotics labs focusing on human-compatible AI and meet with the respective faculty and graduate students in those labs. As the week unfolds, you engage in small-group, self-directed research and/or project-based learning toward presentations on the last day of the program. Your STEM track content wraps up with a closing circle around 3:30 p.m. Afterward, you gather together for additional unique career pathway programming in mixed groups. This can include a U.C. Berkeley campus tour, a current student panel and Q&A, and other personal or professional development workshops. Programming concludes at 5 p.m. If you opt for the residential track, you will stay on campus for dinner and evening activities— both involving social and college preparedness—and then sleep in the U.C. Berkeley dorms.

Jishan Jiang

Jishan Jiang, a rising junior at UC Berkeley, is pursuing a double major in Legal Studies and Data Science, complemented by a minor in Education. She is interested in learning designs, curriculum development, data ethics, educational policies and K-12 STEM education. With aspirations to become an educator and researcher, Jishan aims to harness the transformative power of education to uplift and empower underserved communities.

Jishan grew up in Suzhou, China. In her free time, she enjoys spending time with her cat and cooking with her friends.

Naomi Yonas

Naomi Yonas is a rising Senior studying Electrical Engineering & Computer Science at UC Berkeley. Her specific interests are connecting artificial intelligence, education, and social justice to combat systemic biases. She believes technology should be equitable and accessible for everyone of all backgrounds.

In her free time, she loves to read books, take long outdoor walks, and ponder about anything.

Tim Hurt

Tim Hurt is a science curriculum developer and researcher at the Lawrence Hall of Science. He has been an educator for the past 10 years, has experience teaching all grades K–12, and has led UC Berkeley’s AI4ALL since 2019. He has developed curricula for grades K–12 with materials covering physics, engineering, and space science. He currently works on projects related to developing and researching AI exhibits for the Lawrence Hall of Science. Tim has both an undergraduate degree in Physics and a Masters in Information and Data Science, from the University of California, Berkeley.