Summer 2010
National Academies Study
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The National Academies prepare the ground for a paradigm shift by convening a Committee on the Analysis of Massive Data. Chaired by UC Berkeley's Michael Jordan, the committee develops a broad agenda encompassing computing, inference, and human decision making, based on their study of a wide range of emerging problems in science, technology, and society. The committee's report, Frontiers in Massive Data Analysis, circulates widely in draft and is officially released in 2013, serving as a blueprint for national change.
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Spring 2012
Presidential Big Data Initiative & AMP Lab
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The Obama Administration launches the Big Data Research and Development Initiative to “develop Big Data technologies, demonstrate applications of Big Data, and train the next generation of data scientists.”
In one of Berkeley’s signal contributions, AMP Lab (Algorithms, Machines, and People) receives a $10M National Science Foundation inaugural “Expeditions in Computing” award, advancing the development of the Berkeley Data Analytics Stack. Directed by Michael Franklin, Michael Jordan, and Ion Stoica, the AMP Lab extends the Berkeley tradition of labs crossing systems with data in emerging areas of impact. Out of the AMP Lab will come Apache Spark, Apache Mesos, and Alluxio, as well as multiple start-ups.
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Spring 2012
DataEDGE Conference
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Under Dean Anno Saxenian, the I School launches inagural DataEDGE(link is external) Conference to bring together senior industry and academic leaders for a conversation about the challenges and opportunities created by the rise of big data.
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Spring 2013
Social Sciences Data Laboratory
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The Social Sciences Data Laboratory (D-Lab) opens its doors, redefining Berkeley’s profile in a new era of data-intensive social science research. Led by Cathryn Carson, it offers training, consulting, working groups, and access to datasets, serving students and researchers across Berkeley’s colleges and schools.
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Summer 2013
MIDS
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Berkeley’s School of Information announces its online Master of Information and Data Science(link is external). The multidisciplinary curriculum draws upon computer science, social sciences, statistics, management, and law. Students use the latest tools and analytical methods to work with data at scale and solve real-world problems. It joins the company of several new and renovated on-campus masters programs with a focus on data science, including the Master of Statistics(link is external) and the Master of Engineering(link is external).
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Fall 2013
Simons Institute for the Theory of Computing
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The Simons Institute for the Theory of Computing, established with a grant of $60M from the Simons Foundation, initiates its programs with a semester devoted to theoretical foundations of big data analysis. Led by Richard Karp and centered on the theme of a “computational lens” on the sciences, it swiftly becomes the world’s leading venue for collaborative research in theoretical computer science and its connections to other fields, including the foundations of data science.
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December 2013
Berkeley Institute for Data Science
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The Berkeley Institute for Data Science (BIDS) launches with a major grant from the Gordon and Betty Moore Foundation and the Alfred P. Sloan Foundation. Nobel Laureate Saul Perlmutter, its founding director, spearheads an initiative drawing together faculty from throughout the campus. In collaboration with the University of Washington and New York University, Berkeley anchors the Moore and Sloan Foundations’ Data Science Environments program, transforming the university setting to accelerate data-intensive discovery.
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Spring 2014
Project Jupyter
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Project Jupyter is launched by Fernando Perez, a researcher in Berkeley’s Helen Wills Neuroscience Institute, and a broad team of collaborators across institutions. The evolution of IPython, Jupyter is a non-profit, open-source project that supports interactive data science and scientific computing across all programming languages. Perez later joins the Berkeley Department of Statistics in 2017, while Jupyter becomes an essential tool for data science across disciplines, winning the 2018 ACM Software System award.
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Summer 2014
Data Sciences Education Rapid Action Team
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The Chancellor and Provost convene the Data Sciences Education Rapid Action Team (DSERAT) to design a comprehensive response to growing student and faculty interest in advancing data science education. A team of faculty is charged with “rethinking at a fundamental level what every educated person must know about quantitative reasoning: how to effectively understand, process, and interpret information to inform decisions in their professional and personal lives and as citizens of the world in the 21st century.”
Members:
Cathryn Carson (co-chair), History Bob Jacobsen (co-chair), Physics and Interim Dean, L&S Undergraduate Studies David Culler, EECS Michael Franklin, EECS Michael Jordan, EECS and Statistics AnnaLee Saxenian, Dean, School of Information Jasjeet Sekhon, Political Science and Statistics Bin Yu, Statistics and EECS
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October 2014
Data-Driven Discovery
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Faculty in ecology, astronomy, and microscopy become inaugural investigators in the Gordon and Betty Moore Foundation’s Data-Driven Discovery initiative, created to foster collaboration and across disciplines and enable new types of scientific breakthroughs.
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January 2015
DSERAT Report
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The Data Sciences Education Rapid Action Team issues its recommendations.
These include:
- A foundational lower division course accessible to everyone, with broad applicability, further enriched by “connector” courses in a diverse range of areas,
- A suite of courses that advance the use of data sciences within the broad swath of disciplines available to Berkeley undergraduates,
- A high-quality minor for students who wish to couple data sciences with their major discipline, and
- A data science major for students who want this to be their primary area of study.
Faculty across the campus join with staff and student collaborators in a grass-roots effort to begin designing new courses and programs.
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Spring 2015
Discovery Program
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The emerging Data Science Education Program, the Berkeley Institute for Data Science, and the Undergraduate Research Apprenticeship Program create the Discovery Program to provide undergraduates with more opportunities to engage in hands-on, team-based discovery opportunities. The Data Science Discovery Program grows rapidly, becoming a prime attractor for undergraduate students.
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March 2015
West Big Data Innovation Hub
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The National Science Foundation announces funding for Big Data Regional Innovation Hubs to cultivate multi-sector collaborations among academia, industry, and government. Part of the Big Data Research and Development Initiative, the regional hubs are created to accelerate progress towards addressing societal challenges, enable access to and use of important and valuable available data assets, and foster a national big data ecosystem. UC Berkeley becomes an active partner in the West Big Data Innovation Hub.
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Fall 2015
Foundations of Data Science and Connectors
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The pilot for Data 8: Foundations of Data Science launches with 94 students enrolled. The course, co-taught by Ani Adhikari of Statistics and John DeNero of EECS, and designed by an interdisciplinary team led by Michael Jordan of Statistics and EECS, is meant to be accessible to students of all backgrounds and does not require advanced math or computer programming experience. Data 8 focuses on building an understanding of computational and inferential thinking in the context of real world data and questions.
Offered alongside Data 8 are six complementary “connector” courses that enable students to experience data science in the context and perspective of a variety of disciplines. Pilot offerings include: “Race, Policing, and Data,” “Health, Human Behavior, and Data,” and “How Does History Count?” Berkeley’s Data Science education program finds its first home in the Undergraduate Division in the College of Letters and Science.
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August 2015
DS421
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DS421, a five-year NSF-funded Research Traineeship program, welcomes its first cohort of graduate students. With a focus on Environment and Society: Data Sciences for the 21st Century, the program is led by David Ackerly of Integrative Biology, later passing to Max Auffhammer of Agricultural & Resource Economics. It draws on faculty from eight departments and offers foundational and advanced training, research experiences, and professional development.
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September 2015
Statistics Strategic Plan
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The Department of Statistics prepares its Academic Program Review. Its self-study observes, “The major driving trend in the field of statistics over the last decade has been the rise of ‘data science.’ … We have been taking a leading role in this campus-wide dialog. To continue to take such a role will require us to marshal our internal resources and to pursue partnerships on campus that both exploit our intellectual strength and expose us to critical intellectual challenges.” The department recommends that Berkeley create a new organizational structure bringing together statistics, computing, and their applications.
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November 2015
Faculty Advisory Board
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Chancellor Dirks and Provost Steele convene a campus-wide Data Science Planning Initiative Faculty Advisory Board (FAB) to chart paths of institutional development and frame an integrated strategy for Berkeley’s global leadership in data science.
Members:
Cathryn Carson, History, FAB Chair Lisa García Bedolla, Graduate School of Education and Political Science Francesco Borrelli, Mechanical Engineering Ron Cohen, Chemistry and Earth & Planetary Sciences David Culler, Electrical Engineering & Computer Sciences Rosemary Gillespie, Environmental Science, Policy & Management Sol Hsiang, Goldman School of Public Policy Bob Jacobsen, Physics and L&S Undergraduate Division (Dean) Michael Jordan, Statistics (Chair) and Electrical Engineering & Computer Sciences Susan Marqusee, Molecular & Cell Biology and QB3 (Director) Anno Saxenian, School of Information (Dean) Jas Sekhon, Political Science and Statistics Chris Shannon, Economics and Mathematics Ion Stoica, Electrical Engineering & Computer Sciences Bin Yu, Statistics and Electrical Engineering & Computer Sciences
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January 2016
Data 8 and Connectors
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Data 8 is offered as regular course; enrollment increases to 447, and connector courses grow to 217 students. Using Jupyter notebooks across the curriculum, faculty develop new ways to teach diverse students at scale. Twenty undergraduate majors revise their statistics requirements to accept Data 8, in some cases along with the Statistics 88 connector.
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June 2016
Pedagogy Workshop
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More than 30 UC Berkeley faculty and instructors participate in a week-long course on the approach and curriculum of Data 8. The Pedagogy Workshop includes support for developing connector courses in participants’ disciplines that connect with and build on the Data 8 foundation. The workshop continues to be offered annually as more faculty and lecturers become interested in integrating data into their curricula.
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June 2016
BIDS XDs
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BIDS hosts the inaugural ImageXD event, a workshop connecting researchers across domains to share knowledge about use of image processing data, algorithms, and software. New XDs soon emerge for text analysis (TextXD) and graphs (GraphXD).
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August 2016
FAB Report
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The Faculty Advisory Board issues its report detailing a vision for all aspects of data science at Berkeley, including cross-campus collaboration, faculty hiring, fundraising, and creating a Division to design a campus-scale approach that leverages the University’s academic and institutional strengths. The report envisions an approach that is:
- Deep - “laying the foundations of the field and pushing its conceptual frontiers”;
- Broad – “applying established or emerging technologies and techniques to the wide range of areas or domains”; and
- Rich – “studying the implications of the explosion of data and analysis for ethics, policy, society, and human knowledge.”
Campus leadership opens the report for broad review and comment. Responses include the Divisional Council of the Academic Senate’s endorsement of the creation of a Division and support for “a rapid and aggressive move into the intellectual space of Data Science by the Berkeley campus.”
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Fall 2016
Diversity and Data-enablement
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The Data Science Education Program and D-Lab introduce modules, short explorations into data science embedded in existing courses, from linguistics to sociology to ethnic studies. A series of American Cultures modules begins. Advanced courses in a variety of disciplines are introduced, such as ESPM 157 Data Science for Global Change Ecology, reflecting important research programs and growing out of earlier connector offerings. |
September 2016
Data Scholars
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The Data Science Education Program and Berkeley’s D-Lab partner with student organizers to initiate the Data Scholars program, a community to engage, support, and empower underrepresented students taking Data 8. Student teams supporting the curriculum grow as the Data Science Education Program expands under the aegis of the Undergraduate Division.
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November 2016
Faculty Support
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An interdisciplinary faculty group submits a letter to Chancellor Christ indicating its support for the FAB recommendations, including the creation of a cross-departmental Division. The letter states: “A major strength of the proposal is the opportunity to integrate outstanding faculty beyond computer science and statistics in its intellectual vision.”
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December 2016
Cross-Campus Initiative
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In response to the FAB report and faculty feedback, campus leadership announces next steps in a cross-campus data science initiative, stating, “The campus should invest in a prominent and significant way in data science.” The institutional vehicle is a new Division of Data Sciences, placed at the level of Berkeley’s schools and colleges, to be formed in 2017.
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Spring 2017
Advanced Offerings
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Nearly 100 students enroll in the new Data 100 course, an intermediate level class developed by a multidisciplinary team of faculty that bridges Data 8 and upper level data science courses, addressing the entire data lifecycle. It begins more than doubling every semester. Professor Ani Adhikari introduces Probability for Data Science, initially to 55 students; it grows exponentially in the following years. Enrollment in Data 8 climbs to 695.
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May 2017
Interim Division and Interim Dean
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Interim Executive Vice Chancellor & Provost Christ announces the creation of a Division of Data Sciences with the two-year appointment of Professor of Electrical Engineering and Computer Sciences David Culler as Interim Dean. His responsibilities include bringing together faculty, researchers and students from across campus to foster new initiatives in data-intensive discovery and education. The Data Science Education Program, led by Cathryn Carson, is a major anchor of the new Division.
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August 2017
Data Science Major/BA Committee
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The L&S Data Science Major/BA Committee, which includes faculty from disciplines from across campus, comes together to design a data science major for the College of Letters and Science. The Committee proposes a major that encompasses courses from faculty from a variety of departments with the aim of preparing students for a wide range of professions involving data science and analytics and for graduate studies in related fields.
Committee Members:
Alexei Efros, EECS Alexey Pozdnukhov, Civil and Environmental Engineering Anca Dragan, EECS Ani Adhikari, Statistics Carl Boettiger, ESPM Cathryn Carson, History and Faculty Lead, Data Science Education Program Charis Thompson, Gender and Women’s Studies Daniel Rokhsar, MCB, Physics David Ackerly, Integrative Biology Deborah Nolan, Statistics Deirdre Mulligan, I School, Law Haiyan Huang, Statistics Heather Haveman, Sociology, Business Jack Gallant, Psychology, Neuroscience James Demmel, Math, EECS Jasjeet Sekhon, Political Science, Statistics John DeNero, EECS Joseph Gonzalez, EECS Joseph Hellerstein, EECS Joshua Blumenstock, I School Laurel Larsen, Geography Laurent El Ghaoui, EECS Lisa Barcellos, Public Health, Computational Biology Lisa Garcia Bedolla, Education Michael Jordan, Statistics, EECS, Computational Biology Nicolaas Veldhuis, Near Eastern Studies Paul Grigas, IEOR Paul Waddell, City and Regional Planning Perry de Valpine, ESPM Philip Stark, Statistics Philip Marcus, Mechanical Engineering Ronald Cohen, Chemistry, Earth and Planetary Science Uros Seljak, Physics Zsolt Katona, Business
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October 2017
FODA
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The National Science Foundation awards Berkeley a grant to create the Foundations of Data Analysis Institute (FODA) to bring together core research communities in theoretical statistics, applied mathematics, and theoretical computer science. It is supported by NSF’s TRIPODS Program (Transdisciplinary Research in Principles of Data Science), which was launched to address fundamental open questions in the theoretical underpinnings of data science. It aligns with the first of NSF’s 10 Big Ideas, Harnessing the Data Revolution, intended to frame the foundation’s investments for years to come.
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January 2018
Faculty Advisory Council
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Interim Dean Culler appoints the Data Science Division Faculty Advisory Council to bring perspectives from throughout campus, advise the Interim Dean, and provide a conduit for socializing important issues. The council meets roughly monthly and the tenure is intended to be the remainder of the Interim process.
Members:
Bin Yu, Statistics Cathryn Carson, History Costas Spanos, EECS/EE, CITRIS Dan Fletcher, Bioengineering David Wagner, EECS/CS John Chuang, Information Josh Bloom, Astronomy Josh Goldstein, Demography Karen Chapple, City and Regional Planning Kathy Yelick, EECS/CS, Lawrence Berkeley National Laboratory Lisa García Bedolla, Graduate School of Education, Political Science Louise Mozingo, Landscape Architecture and Environmental Planning, American Studies Max Auffhammer, Agricultural and Resource Economics, International and Area Studies Michael Jordan, EECS/Statistics Pamela Samuelson, Law Ron Cohen, Chemistry, Earth and Planetary Science Susan Marqusee, Molecular and Cell Biology
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January 2018
Human Contexts and Ethics
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New classes are piloted in the area of Human Contexts and Ethics of Data, a universal requirement of the proposed data science major. HCE courses explore the human and social structures, formations, and practices that shape data science activities, from data collection and analysis, to data privacy and security practices, to questions of algorithms and justice. |
February 2018
RISELab
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Berkeley’s RISELab, successor to AMPLab, receives NSF’s Expeditions in Computing Award, providing $10 million in funding over five years to enable game-changing advances in real-time decision making technologies.
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February 2018
Inter-departmental Task Force
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The department chairs of Statistics, Industrial Engineering and Operations Research, and Electrical Engineering and Computer Sciences, along with leaders in science and technology studies, new media, cognitive science, and computational biology, assemble an Interdepartmental Task Force to propose basic principles and explore possible organizational structures for the Division.
The task force recommends the following goals:
- Shared governance and transparency: “To build trust and a joint sense of mission” among the diverse units and disciplines.
- Synergy and cohesion within the Division: “An inclusive culture that respects different disciplinary practices and approaches while emphasizing interdisciplinary collaboration.”
- Tight integration and increased synergy with other units across campus: “...Driven by both shared educational missions and synergistic research goals.”
- New undergraduate program (s): that are “responsive to student needs and the changing intellectual and practical landscape in Data Science.”
- Breadth: Recognition that “faculty slots related to Data Science are spread throughout campus, not restricted to this Division” and that the Division “should nurture and oversee programs that foster the application of Data Science campus-wide and create an environment where all faculty engaged in Data Science can become part of a collaborative community.”
The Task Force proposes circulating its recommendations among a wide group of potentially interested faculty for feedback and convening a smaller task force to draft a more concrete proposal for moving forward that includes this feedback.
Contributors to the Task Force report:
Scott Shenker, EECS/CS, Chair Murat Arcak, EECS/EE Cathryn Carson, History and Science and Technology Studies Sandrine Dudoit, Statistics Jack Gallant, Psychology Robert Glushko, Cognitive Science Philip Stark, Statistics
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March 2018
BA in Data Science
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The Academic Senate approves a Bachelor of Arts in Data Science in the College of Letters and Science. Requirements include courses in human contexts and ethics to help students develop an understanding of the human and social structures, formations, and practices that shape data science activity; and a domain emphasis, or a specialization in one of more than two dozen fields that include data applications.
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April 2018
Data 8X
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Data 8 becomes available on edX in an online Foundations of Data Science sequence as Data 8X. More than 75,000 students enroll. The course is taught by David Wagner, Ani Adhikari, and John DeNero, three recipients of Berkeley's Distinguished Teaching Award. |
April 2018
Ready for Launch
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Campus leadership gives the go-ahead to launch the Data Science Major. In the Division of Data Sciences' Fall 2017 Data Science Survey, 13% of all undergraduates at Berkeley indicated they would be “very likely” to declare as a Data Science major (5/5 on a five-point scale). Departments and faculty across campus take further steps to integrate data science into their own teaching. The National Academies of Sciences, Engineering and Medicine release their study report, “Data Science for Undergraduates: Opportunities and Options,” drawing significantly from the Berkeley developments.
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May 2018
Programs Governance Committee
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The Division of Data Science Degree Programs Governance Committee, a working body of faculty from multiple departments, is formed to oversee the data science major and future minor; review the integration of course offerings; curate course lists; liaise with other units, programs, and majors; and provide a focal point for addressing student and institutional issues.
Committee Members:
David Culler (Chair), Division of Data Sciences Karen Chapple, City & Regional Planning John DeNero (Chair Delegate), EECS Sandrine Dudoit (Chair Delegate), Statistics Ani Adhikari, Statistics David Bamman, Information Rasmus Nielsen, Statistics and Integrative Biology Joe Hellerstein, EECS Carl Boettiger, Environmental Science, Policy & Management (Domain Emphasis) David Harding, Sociology (Domain Emphasis) Cathryn Carson, History (Human Contexts and Ethics) and Faculty Lead, Data Science Education Program Nasser Zakariya, Rhetoric (Human Contexts and Ethics)
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June 2018
HCE Pedagogy Workshop
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A pilot workshop on pedagogy for Human Contexts and Ethics is offered for Berkeley instructors and students, following the model of other summer workshops.
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July 2018
Pedagogy Workshop for All
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The Division of Data Sciences, in partnership with the National Science Foundation, the West Big Data Innovation Hub, and Microsoft offer the first Data Science Pedagogy Workshop open to faculty from other universities and colleges. Three dozen participants from across the US and Canada attend, gaining experience with the Data 8 approach, best practices in curriculum design, and technological infrastructure.
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July 2018
Center for Connected Learning
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UC Berkeley Library, the Division of Data Sciences, and Educational Technology Services create the vision for the Center for Connected Learning, an innovative collider space in Moffitt Library. The beta version of Center provides data science peer advising and consulting, maker workspaces, and VR labs. This creative space, run by student organizations, is designed for students to support other students and encourages shared expertise and community building in the data sciences.
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August 2018
Data Collaboratives
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The Division launches the Data Collaboratives program, a new form of collaboration supported by Schmidt Futures that links students, government, community, and business partners to leverage data to help address complex social problems.
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Fall 2018
5th Year MIDS
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The I School announces 5th Year MIDS(link is external), a pathway to the Master of Information and Data Science for graduating UC Berkeley undergrads, to launch in fall 2019.
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September 2018
Major Open
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With a new advising team in place, students can now declare a data science major. Nearly 1,000 students file pre-declarations in the first eight weeks of advising. |
November 2018
New Division
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Berkeley announces plans for a new division, provisionally named the Division of Data Science and Information. The innovative Division is envisioned to encompass computation, information, and data science and their human, social, political, artistic, and scientific implications. It connects departments from the College of Engineering, the College of Letters and Science, and the School of Information; incorporates the Berkeley Institute for Data Science (BIDS); and establishes a new Data Science Commons that will bring together groups of faculty and students from across the University to open new research domains and develop new fields of study. |
December 2018
UC Berkeley Strategic Plan
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Berkeley announces its ten-year Strategic Plan, investing heavily in data science and integrating it across the campus’ signature initiatives. The Strategic Plan provides the intellectual and organizational framework for Berkeley’s next capital campaign. |
December 2018
First Data Science BA Graduates
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Nine students become Berkeley’s first data science BA graduates. Their domain emphases include cognition, computational biology methods, economics, robotics, social welfare, health and poverty, and applied mathematics and modeling.
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April 2019
Certificate in Applied Data Science
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Academic Senate approves the School of Information to offer a new Graduate Certificate in Applied Data Science to graduate students across the UC Berkeley campus. The Graduate Certificate in Applied Data Science, an Option II Certificate program, introduces the tools, methods, and conceptual approaches used to support modern data analysis and decision making in professional and applied research settings.
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January 2019
Growing DS Enrollment
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To meet student demand, Data 8 expands further, with more than 1,500 students registering for Spring semester. Registration tops 1,000 for Data 100, 900 for Introduction to Machine Learning, 250 for Probability for Data Science, and 200 for Human Contexts and Ethics of Data.
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May 2019
First Data Science Commencement
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More than 100 students graduate with a Bachelor of Arts in Data Science in the first commencement. Kate Johnson, President of Microsoft US, delivers the commencement address at the ceremony at Wheeler Hall Auditorium.
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August 2019
Division's First Associate Provost
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Jennifer Tour Chayes, Microsoft Technical Fellow and Managing Director for Microsoft Research in New England, New York, and Montreal, is named the university’s first Associate Provost for the Division of Data Science and Information and Dean of the School of Information, effective January 2020. In the interim, Dean of Undergraduate Studies Bob Jacobsen is named to serve as division of data science interim dean and Associate Dean John Chuang as head of the School of Information.
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October 2019
Data Science Minor Approved
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The College of Letters & Science, College of Natural Resources, College of Engineering, College of Chemistry, and Haas School of Business approve the new data science minor, a program designed to serve students from a range of majors. The College of Environmental Design approves the minor in November. Along with the entry point of the popular Foundations of Data Science (Data 8) course, the minor incorporates Berkeley's signature classes on Human Contexts and Ethics, which equip students to understand and act on the human and social implications of data.
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November 2019
NSF Grant to Improve Data Science Education
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The National Science Foundation awards Berkeley $3 million to evaluate and extend its data science programs. Based in D-Lab and involving partnerships with Mills College and the University of Maryland, Baltimore County (UMBC), the grant will support Berkeley's efforts to ensure that data science remains accessible to a broad range of students. D-Lab Director David Harding will oversee the project, titled “Undergraduate Data Science at Scale.”
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February 2020
Data Science Minor Eligible to Declare
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UC Berkeley undergraduate students are now able to declare a Minor in Data Science.
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February 2020
Division of Computing, Data Science, and Society
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Paul Alivisatos, Executive Vice Chancellor and Provost, and Jennifer Chayes, Associate Provost, announce the official Division name: Computing, Data Science, and Society.
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February 2020
Seed funding for Data Science Hub
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An anonymous $252 million gift--the largest in Berkeley’s history--provides seed funding for a new home for CDSS.
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