David Culler

The nine data science graduates are Jeevan Mokkala, Emanuel Lucban, Adam Osborn, Nikhil Krishnan, Thao Vo, Alexander Ivanoff, Liam Shi, Howe Cui and Ting Chih Lin. It appears, however, that many students will follow in their footsteps: This fall, when the major officially opened for students to declare, nearly 1,200 filed predeclarations.

UC Berkeley announced Thursday morning that it will create a new campus division, provisionally called the Division of Data Science and Information.

Data 8X, the course’s online equivalent, is free to audit, but students must pay in order to take exams and receive a certificate. This certification, however, will likely not transfer as academic credit or satisfy the data science major requirement, according to Cathryn Carson, the faculty lead of the Data Science Education Program.

At a packed town hall-style meeting Thursday, students and staff gathered to hear presentations and ask questions about UC Berkeley’s data science major and minor program, which program organizers hope to make available next semester.

For many classes, questions asked on “syllabus day” — the first lecture of the semester — relate to administrative issues or course policies. For Data 8, however, a student asked in the very first class if the major would be ready to declare in the near future.

David Culler, a campus electrical engineering and computer sciences professor, has been appointed the interim dean for the newly created Division of Data Science, according to a campus press release.

The campus has created an interim dean position to lead the development of the new Division of Data Science at UC Berkeley, as announced Dec. 19.

As part of a fireside chat hosted by Chancellor Nicholas Dirks, about 20 students gathered at University House on Wednesday to give their input on the trajectory of a pilot data science class.

The new four-unit course, “Foundations of Data Science” — cross-listed as Statistics 94 and Computer Science 94 — combines introductory statistics and computational concepts with hands-on work involving hard data that brings “real-world relevance,” according to the program's website.