Workshops for External Professors
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 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, and the University of Washington, among others.
Led by Professor David Wagner, recipient of the Berkeley Distinguished Teaching Award and Data 8 co-instructor, this workshop is intended for faculty who are actively engaged in developing and offering a data science curriculum.
Click here for more information on the workshop.
Workshops for UC Berkeley Faculty/Graduate Students
Data Science Pedagogy and Practice: A Short Summer Workshop
June 3-5, 2019
Learn data science concepts, pedagogical methods, and technical tools, and get help integrating them into your own practice. This workshop 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.
Registration - Please fill out this interest Form.
Graduate Student Introduction to Data Science Pedagogy
June 7, 2019
In this one-day workshop, graduate students will learn about the pedagogy of the Data Science Education Program. 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.
Registration - Please fill out this Interest Form
Human Contexts and Ethics (HCE) Workshop
2019 Dates Coming Soon
Berkeley’s undergraduate Data Science programs 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 two-day workshop, we aim to encourage and support instructors across the disciplines to develop new courses and transform existing ones to become Human Contexts and Ethics (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.
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. 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.
More information: https://data.berkeley.edu/education/courses/modules
Module Support Request Form: https://goo.gl/zRxVm7
Proposals for Data Science Connector Courses
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.
More information: https://data.berkeley.edu/education/connectors
Connector interest form: https://goo.gl/s9EkN4
Spring 2019 AIS Workshops
Thursday, February 21, 2019 2-3:30 - Academic Innovation Studio, 117 Dwinelle Hall
An illustration of the types of course materials being developed for Data Science pedagogy for a variety of classes, including introductory, intermediate and advanced courses, and American Cultures classes. First hand experiences from instructors adopting and adapting these materials. With the Center for Teaching and Learning.
Using Digital Learning Platforms for Data Science Education for All
Thursday, March 7, 2019 12-1:30 - Academic Innovation Studio, 117 Dwinelle Hall
A brief review of the elements of teaching using Jupyter notebooks and deployment of classes via Jupyterhub. Overview of the introduction of Data Science pedagogy into classes, how these technologies are making data science accessible to all types of students regardless of technical background. Review of the types of Data Science classes at Berkeley. Hands-on computer-demonstrations of data science instructional materials. With the Research IT Reading Group.
(This presentation also is part of a week of campus wide events highlighting ways to foster diversity, equity, and inclusion in data science.)
Graduate Student Introduction to Data Science Pedagogy
Thursday, April 11, 2019 2-3:30 - Academic Innovation Studio, 117 Dwinelle Hall
Instruction for graduate students about using the data science teaching tools such as developing Jupyter notebooks for classes and teaching on a cloud based JupyterHub. Examples of how to support data science teaching in all types of classes. No previous experience necessary, all disciplines encouraged.
Slide Deck - Video of Presentation
If you have questions about the Data Science Education Program in the Division of Data Sciences, feel free to contact us:
Cathryn Carson (firstname.lastname@example.org), DSEP Faculty Lead
Eric Van Dusen (email@example.com), DSEP Curriculum Coordinator
David Culler (firstname.lastname@example.org), Interim Dean, Division of Data Sciences