Academic Resources Kit (ARK) for Instructors

For UC Berkeley Instructors

The Division of Data Sciences's Academic Resource Kit (ARK) for Instructors has several near-term opportunities to support instructors in learning and incorporating data science approaches. We are offering three summer workshops, and two programs of course development resources. 

Program Overview

Building from the freshman level upwards, the Division of Data Sciences supports an open, interdisciplinary curriculum that stretches across campus and provides a foundation for Berkeley undergraduates of all majors to engage capably and critically with data. The Foundations of Data Science class (Data 8) is currently serving over 1,000 students per year across about 70 majors and fulfills statistics requirements in 90 percent of the majors that have one. More than 30 entry-level “connector” courses have been created by instructors in disciplines from humanities to engineering. Instructors in many departments are now developing advanced courses in order to serve their existing majors, and to integrate with the major and minors to be offered through the Division of Data Sciences.

Summer 2018 Workshops

Data Science Pedagogy and Practice: A Short Summer Workshop

Monday-Thursday, June 4-7, 2018 | Academic Innovation Studio, 117 Dwinelle Hall

Learn data science concepts, pedagogical methods, and technical tools, and get help integrating them into your own practice. This workshop (June 4-6, with curriculum building meetings on June 7 tuned to your individual curricular needs) will cover some of the computational and statistical concepts that students learn in the Foundations of Data Science class (Data 8) through hands-on analysis of real-world data. It will support instructors from all disciplines in exploring how to teach courses that can connect with and enrich this approach. Open to UC Berkeley instructors, faculty, graduate students, postdocs, and other members of the campus community as space permits. No computational or statistical background required.

More information: http://data.berkeley.edu/education-program/data-science-pedagogy-workshop

Workshop registration: https://goo.gl/N28TWb

Contact: Ryan Edwards at ryanedw@berkeley.edu

Graduate Student Introduction to Data Science Pedagogy

Friday, June 8, 2018 | Academic Innovation Studio, 117 Dwinelle Hall

In this new one-day workshop, graduate students will learn about the pedagogy of the Data Science Education Program, where UC Berkeley is leading in curricular innovation in this exciting area. This workshop will cover some of the computational and statistical concepts that students learn in Data 8 and Data 100, as well as an overview of the Connector courses and Modules. It will also give experience using a cloud based computing environment. Graduate students can use these skills and resources to improve and imagine new types of teaching. Open to all UC Berkeley graduate students.

More information: https://data.berkeley.edu/news/graduate-student-data-science-pedagogy-workshop 

Workshop registration: https://goo.gl/4j6FyH

Contact: Eric Van Dusen at ericvd@berkeley.edu

Human Contexts and Ethics (HCE) Workshop

Monday-Tuesday, June 11-12, 2018 | Academic Innovation Studio , 117 Dwinelle Hall

Berkeley’s undergraduate Data Science programs will include a requirement for students to learn about the human, social, and ethical contexts in which data analytics and computational inference play a central role. With this 2-day workshop we aim to encourage and support instructors across the disciplines to develop new courses and transform existing ones to become HCE options. The workshop will discuss the framing of the HCE requirement, review experience so far, and give support in developing new modes of pedagogy.  We’ll cover approaches such as case studies, historical examples, data sources, and exercises.

More information: https://data.berkeley.edu/news/new-human-contexts-and-ethics-hce-workshop

Workshop registration: https://goo.gl/NzyWEp

Contact: Cathryn Carson clcarson@berkeley.edu

Continuing Opportunities

Data Science Modules - Request Development Support

The Data Science Education Program provides assistance to instructors interested in adding data science modules to their existing classes, through student developer teams that partner closely with you to develop materials over the summer and into Fall 2018. Data science modules are short explorations that give students the opportunity to work hands-on with a dataset relevant to your course and receive instruction on the principles of data analysis, statistics, and computing. Modules vary widely and are customized based on each instructor’s objectives and the type of course, ranging in length from one to two lectures to multiple-session workshops culminating in a data-centered project. A recent article and video explain how modules are currently being deployed.

For more information visit: https://data.berkeley.edu/education/courses/modules

Module Support Request Form: https://goo.gl/zRxVm7

Proposals for Data Science Connector Courses (Fall or Spring)

Students in Data 8 learn computational and statistical concepts from a variety of examples spanning a broad range of disciplines. Connector courses (2, 3, or 4 units, often numbered 88) are designed to build on students’ analytical knowledge from Data 8 in connection to their own interests in a specific field. Connectors can be housed in a department, cross-listed in multiple programs, or piloted as a L&S course. The Data Science Education Program seeks to broaden the suite of connector offerings available to students and increase the potential to integrate data science into existing curricula. DSEP is able to provide a range of technical, pedagogical, financial, and community-building support to you in piloting a course, as well as computer lab space and lab assistants.

For more information visit: https://data.berkeley.edu/education/connectors

Connector interest form: https://goo.gl/s9EkN4

Contact us

If you have questions about the Data Science Education Program in the Division of Data Sciences, feel free to contact us:
Cathryn Carson (clcarson@berkeley.edu), DSEP Faculty Lead
Ryan Edwards (ryanedw@berkeley.edu), DSEP Curriculum Coordinator - Connectors
Eric Van Dusen (ericvd@berkeley.edu), DSEP Curriculum Coordinator - Modules
David Culler (culler@berkeley.edu), Interim Dean, Division of Data Sciences

For Instructors in Partner Institutions

UC Berkeley welcomes inquiries about how to design and implement a broad-based data science program. Below please find resources for further exploration into our undergraduate data science curriculum. 

Please fill out this interest form(link is external) so that we can direct you to the resources you need. 

University Partners

  • Yale 
  • Cornell
  • University of Washington
  • Columbia
  • UCSB
  • Spelman College
  • University of British Columbia

Workshop on Undergraduate Data Science Pedagogy & Practice July 16 - 19th, 2018

Meet with over 35 faculty from around the country to learn about the Berkeley Data Science Curriculum and share notes. 

Curriculum

Our website at data.berkeley.edu provides a wealth information about our program, including a curriculum overviewlist of courses offered, news, and more. Our original design document may be helpful if you are developing your own program. Feel free to contact us to learn more.

Foundations of Data Science (Data 8)

  • Zero to Data Guide - Comprehensive guide to how to deploy a Data 8 like course into your institution. 

Connector Courses

For more information about the Connector Courses in many fields that “connect” to Data 8, please visit our list of all connectors that have been offered. Connectors are taught by instructors from many different domains with varying degrees of data science experience. Individual instructors may be willing to answer questions about their courses if you contact them individually.

Jupyter Hub

JupyterHub is a tool that allows Berkeley’s data science program to quickly utilize cloud computing infrastructure to manage a hub that enables users to interact remotely with a specific computing environment. JupyterHub offers a useful way to standardize the computing environment of a group of people (e.g., for a class of students), as well as allowing people to access the hub remotely.

To learn about creating a JupyterHub, please review this documentation:

https://zero-to-jupyterhub.readthedocs.io/en/latest/

Thank you for your interest in the Berkeley Data Science curriculum!