2019 National Workshop on Data Science Education

Time: June 24-27, 2019

Location:  Chou Hall, UC Berkeley

UC Berkeley has pioneered an innovative undergraduate “Foundations of Data Science” curriculum 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, “modules” that introduce data science into existing courses across campus, and complementary courses on ethics and human contexts taught by humanities and social science faculty. Several universities have incorporated aspects of this novel curriculum into their data science programs, including Cornell, Yale, and the University of Washington, among others.

Led by Professor Ani Adhikari and David Wagner, both recipients of the Berkeley Distinguished Teaching Award and Data 8 co-instructors, this workshop is intended for faculty who are actively engaged in developing and offering a data science curriculum.

The workshop is made possible by support from the 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 these education approaches and ways to translate them to your institution.:

Foundations of Data Science

Designing a curriculum built on computational thinking with Python, inferential thinking by resampling, prediction, and machine learning.

Data Science Modules

How to infuse data sciences lectures, labs, assignments, and student projects into any domain area. 

Human Contexts and Ethics 

Exploring how human, social, and institutional structures and practices shape technical work around computing and data, as well as how data and computing permeate and shape our lives.

Technology Infrastructure

The technology underlying the pedagogy platform (JupyterHub, Kubernetes) and how to replicate it.

Schedule

All workshop sessions will be held at Chou Hall N340/344 unless otherwise stated.

Monday, June 24

12:00 PM

Welcome Lunch - Registration and Informal Gathering 

1:15 PM

Welcome - Data Science Campus Engagement (Cathryn Carson)

1:30 PM

Welcome - Workshop Vision & Overview (Eric Van Dusen)      

1:45 PM

Data 8 Overview (Ani Adhikari)

2:30 PM

Coffee Break

2:45 PM

Pedagogy of Data 8 (Ani Adhikari)

4:00 PM

National Landscape Talk and Group Discussion (David Culler) 

5:00 PM 

Reception @ Hearst Mining Building 

Tuesday, June 25

9:00 AM 

Inference and Estimation (Will Fithian)

10:30 AM 

Coffee Break

10:45 AM

Data 8 Lab

12:00 PM

Lunch

1:00 PM

Lightning Talks Session 1 

2:00 PM

Overview of Data Science Modules and Connectors (Eric Van Dusen)

2:30 PM 

Coffee Break

2:45 PM

Module Demos

4:00 PM

Infrastructure Session 1

5:00 PM

Demo: Build your own Notebook - Chris Pyles 

Wednesday, June 26

9:00 AM

Prediction and Machine Learning (David Wagner)                         

10:30 AM

Coffee Break

10:45 AM

Data 100 (Deb Nolan)                                          

11:30 AM

Human Contexts and Ethics (Ari Edmundson)                                                  

12:00 PM 

Lunch

1:00 PM

Lightning Talks Session 2

2:00 PM 

Designing of Major and Minor - Institutional (Cathryn Carson)

2:30 PM

Coffee Break

2:45 PM

Infrastructure Session 2

4:00 PM

Student Teams Presentations and Student Panel (Anthony Suen) 

5:00 PM

Demo: Build your own The Littlest Jupyterhub  (Yuvi Panda) 

Thursday, June 27

9:00 AM 

Lightning Talks Session 3       

10:00 AM

Unconference Session 1                             

10:30 AM

Coffee Break

10:45 AM

Unconference Session 2

11:15 AM

Community of Practices Next Steps (Cathryn Carson)                                  

Questions

For questions please email: ds-help@berkeley.edu(link sends e-mail)