Almost all major programs with a statistics requirement at Berkeley have approved the use of data science courses as a means of satisfying their existing requirement, as proposed by the Chair of Statistics, Michael Jordan. A few majors with an existing statistics requirement are working through their particular approval process.
As of Saturday morning January 16, 479 students were signed up for the 481 total seats available in the first regular offering of Foundations of Data Science. We are excited to see this broad, diverse cohort - and at the same time be able to accommodate the high level of student interest in this very new offering. Universities throughout the world are watching the development of this course and the connections to the many disciplines, reflected in the connector courses, that is the essence of data science.
All of the connector courses for Spring 2016 have now been approved by the UC Berkeley committee on courses and instruction. And a new connector, STAT 89B, Introduction to Matrices and Graphs in Data Science, has been added to the program, bringing the total up to eleven connectors. All of these are designed to be suitable to take concurrently with the Foundations course. So, to the nearly 500 of you in the Foundations Course and the 109 who took the fall pilot, please enjoy these wonderful data science connections to an exciting world of data.
On December 3 a large group of students (https://www.facebook.com/events/1667555180157662/) joined Professor John DeNero, along with several connector instructors, for an information session about the new UC Berkeley Data Science Undergraduate Education Program.
Video of the infosession
I'm writing, in my role as Chair of the Department of Statistics, with respect to CS/INFO/STAT c8 and the course STAT 2, which for many years has met the requirement for an introductory course on statistical inference in a variety of majors at Berkeley. While our department will continue to offer STAT 2 for the foreseeable future, I also want to make you aware of a new course, entitled "Computational Thinking and Inferential Thinking: Foundations of Data Science." We believe that this course would serve many of your students as well as STAT 2; indeed, for many students we think that the new course would be a better option. We would like to encourage you to consider changing your requirements to include STAT c8 in addition to STAT 2 as meeting your statistics requirement, and to make your students aware of this new option.
Lecture will be held on Mondays with labs to follow on Monday and Tuesday. No meetings in the first week of the term, as Jan 18 is a holiday. Meet c8 first and then join CS88 ready to get coding.
The Foundations of Data Science course provides a baseline of computing skills, statistical concepts, and data visualization, including basic geospatial data presentation. This connector extends those aspects in the geospatial domain and augments them with concepts that are rather specific to this domain. It has both an application of data science aspect and a technical depth aspect. During the first three weeks of the term, the connector provides a background in geospatial analysis, while the main course develops a body of computational and statistical skills.
In this course students will apply methods learned in the Foundations course to explore, pose, and answer key questions using relevant data from the Ecological and Environmental Sciences. In so doing, students will confront the complexity and messiness of real world data, and learn and practice essential tools for capturing, manipulating and sharing data. We will further take advantage of the small class setting provided by the connector to emphasize good workflow and coding practice, collaboration, and help students better master and apply the techniques covered in the Foundation.
A team of students are working closely with the Cal community to understand how best to develop a Data Science program the contributes to the student experience @ Cal. Led by Data Science Fellow and I-School alum Anthony Suen, they have organized themselves into four study teams.
If you'd like to get in touch with them, send email to email@example.com.