Time: July 16-19, 2018
Location: Social Science Matrix, 8th Floor, Barrows Hall, UC Berkeley
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. 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.
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.
The workshop is made possible by support from the National Science Foundation, Microsoft Corporation, the West Big Data Innovation Hub, and UC Berkeley's Division of Data Sciences.
Participants will come away with an in-depth understanding of:
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Foundations of Data Science curriculum built on computational thinking with python, inferential thinking by resampling, prediction and machine learning.
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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.
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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.
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How the material is delivered in lectures, labs, assignments and student projects.
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The pedagogical theory underlying the integrated computing and statistics curriculum.
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Technology foundations underlying the pedagogy platform and how to replicate it.
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What it would take to translate the education approach and platform to your institution.
Schedule
All locations will be on the 8th floor of Barrows Hall unless otherwise stated.
Monday July 16 |
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Time |
Session |
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12:00pm |
Welcome Lunch |
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1:00pm |
|
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2:00pm |
|
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2:30pm |
Break |
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2:45pm |
|
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3:00pm |
|
|
3:30pm |
Break |
|
3:45pm |
Group Discussion: Building Data Science Curricula at Your Institution (David Culler) |
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5:00pm |
Welcome Reception at the Berkeley Institute for Data Sciences (David Mongeau) Orianna DeMasi, Andreas Zoglauer, Diya Das, Johannes Schoneberg |
Tuesday July 17 |
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9:00am |
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9:45am |
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10:30am |
Break |
|
10:45am |
|
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11:15am |
|
|
11:45am |
Lunch |
|
1:00pm |
|
|
1:45pm |
Infrastructure: Piazza, Attendance, Gradescope, Git, Notebooks, Creating Assignments |
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2:15pm |
Break |
|
2:30pm |
|
|
3:15pm |
Break |
|
3:30pm |
|
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4:00pm |
Group discussion: Models, Reflections, and Challenges for Intro-level Pedagogy |
Wednesday July 18 |
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9:00am |
Connectors, Modules, and Data-Enabled Courses (Eric Van Dusen) |
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10:00am |
|
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11:00am |
Break |
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11:15pm |
Data science major, minor, and program (Cathryn Carson) |
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12:00pm |
Lunch |
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1:00pm |
Lightning Talks 1: Visitor Presentations (Moderator: Anthony Suen) |
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2:00pm |
|
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3:00pm |
Break |
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3:15pm |
Student Panel (Students from Data 8 and Other DS courses) |
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4:15pm |
Lightning Talks 2: Visitor Presentations and Discussion (Moderator: Anthony Suen) |
Thursday July 19 |
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9:00am |
|
|
10:00am |
Break |
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10:15am |
Group Breakout Reflection Session (Cathryn Carson) |
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11:15am |
Open Discussion: What Does it take to Move Forward? |
Questions
For questions please email: ds-help@berkeley.edu