About the Program
The Master of Information Management and Systems (MIMS) program is a two-year full-time program, designed to train students in the skills needed to succeed as information professionals. Such professionals must be familiar with the theory and practice of storing, organizing, retrieving, and analyzing information in a variety of settings in business, the public sector, and the academic world. Technical expertise alone is not sufficient for success; I School graduates will be expected to perform and manage a multiplicity of information-related tasks.
Graduates of the MIMS program will be able to:
- Identify and address user and stakeholder information and resource needs in context.
- Make and assess information design decisions iteratively.
- Intentionally organize collections of information and other resources to support human and/or machine-based interactions and services.
- Understand and apply foundational principles and debates of information law, policy, and ethics.
- Analyze complex relationships and practical choices at the intersection of technical design, policy frameworks, and ethics.
- Understand and apply fundamental principles and debates of information economics.
- Understand and apply architectural, computational, and algorithmic thinking and principles of concurrency to the design of information systems.
- Scope, plan, and manage open-ended projects, both individually and in teams.
- Present findings and conclusions persuasively.
Such a profession is inherently interdisciplinary, requiring aspects of computer science, cognitive science, psychology, sociology, economics, business, law, library/information studies, and communications.
The I School also offers a master's in Information and Data Science (MIDS), a master's in Information and Cybersecurity (MICS), and a doctoral degree (PhD) program in Information Management and Systems.
Admission to the University
Minimum Requirements for Admission
The following minimum requirements apply to all graduate programs and will be verified by the Graduate Division:
- A bachelor’s degree or recognized equivalent from an accredited institution;
- A grade point average of B or better (3.0);
- If the applicant has completed a basic degree from a country or political entity (e.g., Quebec) where English is not the official language, adequate proficiency in English to do graduate work, as evidenced by a TOEFL score of at least 90 on the iBT test, 570 on the paper-and-pencil test, or an IELTS Band score of at least 7 on a 9-point scale (note that individual programs may set higher levels for any of these); and
- Sufficient undergraduate training to do graduate work in the given field.
Applicants Who Already Hold a Graduate Degree
The Graduate Council views academic degrees not as vocational training certificates, but as evidence of broad training in research methods, independent study, and articulation of learning. Therefore, applicants who already have academic graduate degrees should be able to pursue new subject matter at an advanced level without the need to enroll in a related or similar graduate program.
Programs may consider students for an additional academic master’s or professional master’s degree only if the additional degree is in a distinctly different field.
Applicants admitted to a doctoral program that requires a master’s degree to be earned at Berkeley as a prerequisite (even though the applicant already has a master’s degree from another institution in the same or a closely allied field of study) will be permitted to undertake the second master’s degree, despite the overlap in field.
The Graduate Division will admit students for a second doctoral degree only if they meet the following guidelines:
- Applicants with doctoral degrees may be admitted for an additional doctoral degree only if that degree program is in a general area of knowledge distinctly different from the field in which they earned their original degree. For example, a physics PhD could be admitted to a doctoral degree program in music or history; however, a student with a doctoral degree in mathematics would not be permitted to add a PhD in statistics.
- Applicants who hold the PhD degree may be admitted to a professional doctorate or professional master’s degree program if there is no duplication of training involved.
Applicants may apply only to one single degree program or one concurrent degree program per admission cycle.
Required Documents for Applications
- Transcripts: Applicants may upload unofficial transcripts with your application for the departmental initial review. Unofficial transcripts must contain specific information including the name of the applicant, name of the school, all courses, grades, units, & degree conferral (if applicable).
- Letters of recommendation: Applicants may request online letters of recommendation through the online application system. Hard copies of recommendation letters must be sent directly to the program, by the recommender, not the Graduate Admissions.
Evidence of English language proficiency: All applicants who have completed a basic degree from a country or political entity in which the official language is not English are required to submit official evidence of English language proficiency. This applies to institutions from Bangladesh, Burma, Nepal, India, Pakistan, Latin America, the Middle East, the People’s Republic of China, Taiwan, Japan, Korea, Southeast Asia, most European countries, and Quebec (Canada). However, applicants who, at the time of application, have already completed at least one year of full-time academic course work with grades of B or better at a US university may submit an official transcript from the US university to fulfill this requirement. The following courses will not fulfill this requirement:
courses in English as a Second Language,
courses conducted in a language other than English,
courses that will be completed after the application is submitted, and
courses of a non-academic nature.
Applicants who have previously applied to Berkeley must also submit new test scores that meet the current minimum requirement from one of the standardized tests. Official TOEFL score reports must be sent directly from Educational Test Services (ETS). The institution code for Berkeley is 4833 for Graduate Organizations. Official IELTS score reports must be sent electronically from the testing center to University of California, Berkeley, Graduate Division, Sproul Hall, Rm 318 MC 5900, Berkeley, CA 94720. TOEFL and IELTS score reports are only valid for two years prior to beginning the graduate program at UC Berkeley. Note: score reports can not expire before the month of June.
Where to Apply
Visit the Berkeley Graduate Division application page.
Admission to the MIMS Program
The I School’s Master of Information Management and Systems (MIMS) program welcomes students from a diverse set of backgrounds; some will be technically educated, some educated in the humanities and social sciences. Our goal each year is to bring in a talented class of students from a broad range of academic and professional backgrounds.
Applications are evaluated holistically on a combination of grade point average, GRE/GMAT score, work experience, statement of purpose, and letters of recommendation. As much as possible, applicants are judged on a combination of these factors. A minimum of two years of job experience is preferred, although not required. All successful applicants must have statements of purpose that demonstrate goals and interests consistent with the mission of the I School.
To be eligible to apply to the Master of Information Management and Systems program, applicants must meet the following requirements:
A bachelor's degree or its recognized equivalent from an accredited institution.
Superior scholastic record, normally well above a 3.0 GPA.
Successful work experience in relevant fields.
Clear indication of professional career goals and reasons for seeking the degree, described in the Statement of Purpose.
For applicants whose academic work has been in a language other than English, the Test of English as a Foreign Language (TOEFL) or International English Language Testing System (IELTS).
Programming competency and proficiency.
For further information and application instructions, please visit the School of Information Application Instructions page.
Master's Degree Requirements
The Master of Information Management and Systems (MIMS) program requires at least 48 semester units of study. The first year of the program consists mostly of a core curriculum; the second year involves further study in core areas along with additional electives, with the expectation that the student will specialize in particular aspects of information management and systems, as well as complete a final project requirement.
|INFO 202||Information Organization and Retrieval||3|
|INFO 203||Social Issues of Information||2|
|INFO 205||Information Law and Policy||2|
|INFO 206A||Introduction to Programming and Computation||2|
|INFO 206B||Introduction to Data Structures and Analytics||2|
|Elective: Additional two- or three-unit course, taken from an approved list of technology courses||2-3|
|INFO 247||Information Visualization and Presentation||4|
|INFO 251||Applied Machine Learning||4|
|INFO 253A||Front-End Web Architecture||3|
|INFO 253B||Back-End Web Architecture||3|
|INFO 256||Applied Natural Language Processing||3|
|INFO 257||Course Not Available||3|
|INFO 259||Natural Language Processing||4|
|INFO C262||Theory and Practice of Tangible User Interfaces||4|
|INFO C265||Interface Aesthetics||3|
|INFO 290T||Special Topics in Technology||1-4|
|Social Science and Policy Requirement|
|Elective: Two- or three-unit course, taken from an approved list of courses.||2-3|
|INFO 232||Applied Behavioral Economics for Information Systems||3|
|INFO 233||Social Psychology and Information Technology||3|
|INFO 234||Information Technology Economics, Strategy, and Policy||3|
|INFO 239||Technology and Delegation||3|
|INFO 271B||Quantitative Research Methods for Information Systems and Management||3|
|INFO 272||Qualitative Research Methods for Information Systems and Management||3|
|Further courses to satisfy the 48 unit requirement may be chosen from the school's course catalog. Up to 40 units of the 48 must be INFO courses. An additional 8 units may be used from courses in other departments, with approval from student's faculty adviser.||25+|
|INFO 298A||Directed Group Work on Final Project||3|
During the summer between the two years, students are strongly encouraged to participate in an internship program in order to use their newly acquired skills in real-world settings. Assistance in arranging internships will be provided whenever possible, but the ultimate responsibility of obtaining the internship will be that of the student. Past internships have been in corporate, academic, government, and nonprofit institutions.
Please refer to the School of Information website for more information.
Faculty and Instructors
* Indicates this faculty member is the recipient of the Distinguished Teaching Award.
Morgan Ames, Assistant Adjunct Professor. Science and technology studies; computer-supported cooperative work and social computing; education; anthropology; youth technocultures; ideology and inequity; critical data science.
David Bamman, Assistant Professor. Natural language processing, computational social science, machine learning, digital humanities.
Joshua Blumenstock, Associate Professor. Machine learning, development economics.
Jenna Burrell, Associate Professor. Technology appropriation in non-Western societies, technology and socio-economic development, qualitative research methods.
Jennifer Chayes, Associate Provost, Division of Computing, Data Science, and Society; Dean, School of Information; Professor . Machine learning and its applications in cancer immunotherapy, ethical decision-making, and climate change.
Coye Cheshire, Professor. Sociology, trust, social media, social psychology, social networks, collective action, social exchange, information exchange, social incentives, reputation, internet research, online research, online dating, online behavior.
John Chuang, Professor. Computer networking, computer security, economic incentives, ICTD.
Paul Duguid, Adjunct Professor. Trademark, information, communities of practice.
Hany Farid, Professor. Digital Forensics, Image Analysis, and Human Perception.
Daniel Gillick, Assistant Adjunct Professor. Natural Language Processing, machine learning, artificial intelligence, statistics, speech recognition.
Morten Hansen, Professor. Creating great companies, collaboration, corporate transformation, leadership.
Marti A. Hearst, Professor. Information retrieval, human-computer interaction, user interfaces, information visualization, web search, search user interfaces, empirical computational linguistics, natural language processing, text mining, social media.
Chris Jay Hoofnagle, Adjunct Professor. Internet law, information privacy, consumer protection, cybersecurity, computer crime, regulation of technology, edtech.
Douglas Alex Hughes, Assistant Adjunct Professor. Experiments and Causal Identification, Social Networks, Political Behavior and Outcomes.
Paul Laskowski, Adjunct Assistant Professor. Information economics, telecommunications policy, network architecture, innovation.
Clifford Lynch, Adjunct Professor.
Jeffrey K. MacKie-Mason, University Librarian and Chief Digital Scholarship Officer, Professor. Incentive-centered design, competition and antitrust policy in information-technology related industry.
Deirdre Mulligan, Associate Professor. Privacy, fairness, human rights, cybersecurity, technology and governance, values in design.
Geoffrey D. Nunberg, Adjunct Professor. The theory, history and social role of information .
Aditya Parameswaran, Assistant Professor. Data management, interactive or human-in-the-loop data analytics, information visualization, crowdsourcing, data science.
Zach Pardos, Assistant Professor. Education Data Science, Learning Analytics, Big Data in Education, data mining, Data Privacy and Ethics, Computational Psychometrics, Digital Learning Environments, Cognitive Modeling, Bayesian Knowledge Tracing, Formative Assessment, Learning Maps, machine learning.
David Reiley, Adjunct Professor. Field experiments, advertising, auctions and other pricing mechanisms, charitable fundraising, and electronic commerce.
Michael Rivera, Assistant Adjunct Professor. Research design, political science, voting and political behavior, technology and politics, civic participation and social media.
Kimiko Ryokai, Associate Professor. Human-computer interaction, tangible user interfaces.
Niloufar Salehi, Assistant Professor. Computer-mediated communication, human-computer interaction.
Annalee Saxenian, Professor. Innovation, information management, entrepreneurship, Silicon Valley, regional economic development, high skilled immigration, Asian development.
Steven Weber, Professor. Political science, international security, international political economy, information science.
Luis Aguilar, Lecturer.
Olukayode Segun Ashaolu, Lecturer.
Sara Cambridge, Lecturer.
Steven Fadden, Lecturer.
Jez Humble, Lecturer.
Xavier Malina, Lecturer.
Nick Merrill, Lecturer.
Fred Nugen, Lecturer.
James Reffell, Lecturer.
Stephen Trush, Lecturer.
Peter Frank Weis, Lecturer.
Michael Buckland, Professor Emeritus. Information management, information retrieval, metadata, library services.
Michael D. Cooper, Professor Emeritus. Analysis, design, database management systems, implementation and evaluation of information systems, computer performance monitoring and evaluation, and library automation.
William S. Cooper, Professor Emeritus.
M. E. Maron, Professor Emeritus.
Nancy A. Van House, Professor Emeritus. Digital libraries, science, information management, technology studies, knowledge communities, user needs, information tools, artifacts, participation of users.