Data Science Education Webinar (John Denero)

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Over 100 thought leaders from organizations around the U.S. and four continents generated innovations in technology, and teaching and learning at the Concord Consortium’s first Data Science Education Technology conference in February 2017. We continue to gather thought leaders in data science education through a series of webinars.

Title: The Data Science Major at UC Berkeley

Blurb: In 2018, UC Berkeley launched a data science undergraduate major structured around its first-year Foundations of Data Science course (data8.org) and upper-division Principles and Techniques of Data Science course (ds100.org). These core courses are now some of the most popular on campus, with thousands of students enrolling each year. A host of connected courses have been developed concurrently at Berkeley, allowing us to offer a Data Science major program that has been designed largely from scratch to support cross-disciplinary, data-driven, computation-intensive inquiry as the central activity in our undergraduate educational experience. This webinar will include a description of some of our courses and course materials, as well as a detailed exploration of example Data 8 and Data 100 lab materials.

Bio: John DeNero is the Giancarlo Teaching Fellow in the UC Berkeley EECS department. He joined the Cal faculty in 2014 to focus on undergraduate education in computer science and data science. He teaches and co-develops two of the largest courses on campus: introductory computer science for majors and introductory data science. He is the author of Composing Programs and co-author of Computational and Inferential Thinking, two online textbooks. His research focuses both on natural language processing and computer science education. He received his Masters in Philosophy from Stanford University and his PhD in Electrical Engineering and Computer Science from UC Berkeley in 2010. Prior to becoming a professor, John was a senior research scientist at Google working primarily on Google Translate and natural language processing.

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