Time: July 16-19, 2018
Location: University of California, Berkeley
Application deadline Monday May 21
UC Berkeley has pioneered an innovative undergraduate “Foundations of Data Science” curriculum (http://data8.org) that takes an integrated approach to introductory computer science and statistics, allowing students to use data-driven methods to think critically about the world, draw conclusions from data, and effectively communicate results. Without reliance on prior computing experience or advanced mathematics prerequisites, it builds from data visualization to non-parametric hypothesis testing and principles of machine learning, all in the context of real-world explorations. Students learn the material through an open-source ‘live’ textbook and a series of hands-on ‘computational notebooks’, delivered through a unique cloud-based technology platform that both avoids barriers to student participation and permits scalability.
Starting in 2015 with a hundred students and growing to over a thousand per semester in 2017, Data 8 became UC Berkeley’s fastest growing course, serving students from 75 majors across the University. Curriculum innovation accompanying the course is further developed in domain area “connector” courses that complement Data 8 concepts and “modules” that introduce data science into existing courses across campus. Several universities have incorporated aspects of this novel curriculum into their data science programs, including Cornell, Yale, University of Washington, and others. This workshop is designed to support faculty interested in translating the Berkeley introductory data science curriculum into their own program.
Led by Professor David Wagner, recipient of the Berkeley Distinguished Teaching Award and Data 8 co-instructor, this workshop is intended for faculty in US bachelor’s degree granting institutions, who are actively engaged in developing and offering a data science curriculum.
Participants will come away with an in depth understanding of:
Foundations of Data Science curriculum built on computational thinking with python, inferential thinking by resampling, prediction and machine learning.
Conveying how to interpret and communicate data and results using a diverse array of real data sets including economic data, geographic data and social networks.
Guiding students in understanding how information will be incomplete and somewhat uncertain, yet inference methods can help quantify uncertainty and establish the accuracy of estimates.
How the material is delivered in lectures, labs, assignments and student projects.
Pedagogical theory underlying the integrated computing and statistics curriculum.
Technology foundations underlying the pedagogy platform and how to replicate it.
What it would take to translate the education approach and platform to your institution.
The three and a half day workshop will be held in Berkeley on the UC campus from the afternoon of Monday, July 16 to the morning of Thursday July 19 to allow for travel on both days. Lodging and some meals will be provided. Limited travel funding is available. Participation is limited to 25 applicants.
To apply to attend the workshop, please complete the application form linked below by Monday, May 21. Notification of selected participants will be provided by Friday, May 25.
The workshop is made possible by support from the National Science Foundation, Microsoft Corporation, and the University of California, Berkeley Division of Data Sciences.
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