Course Schedule: Fall 2012

Lower-Division Courses

Instructor(s): Brian Carver
Time: DIS Sec. 1 F 10-11, DIS Sec. 2 F 11-12, Dis Sec. 3 F 1-2, and DIS Sec, 4 F 2-3
Location: 107 South Hall
CCN: 42502

This lower-division survey course will provide an introduction to the study of information, an interdisciplinary science that draws on aspects of computer science, sociology, economics, business, law, library studies, cognitive science, psychology, and communication. This course will introduce major issues involved with the science and management of primarily digital information and prepare students for more advanced courses in the field. The course is organized into modules that may cover topics such as social bookmarking, networks and web security, human-computer interaction, interface design, technology and poverty, law and policy, business models, and entrepreneurship. Students will develop their research, evaluation, analysis, and synthesis skills and demonstrate these through completing a course-long group project addressing an information problem of their group's choice.

Students from most disciplines will be interested in the topics covered in this course and will find the course objectives valuable when applied to their own fields. Additionally, students who are interested in the field of information studies will take this course in order to be introduced to the key concepts as well as future graduate studies at schools of information.

Course Format:
Info 10 is a fully web-based course. Lectures will be available online, but will not be assigned a particular time or classroom. Discussion sections meet online at the assigned times.

Instructor(s): Yale Braunstein
Time: TuTh 2-3:30
Location: 202 South Hall
CCN: 42503

An introduction to high-level computer programming languages covering their basis in mathematics and logic. This course will guide students through the elements that compose any programming language including expressions, control of flow, data structures, and modularity via functions and/or objects. Covers traditional and contemporary programming paradigms including sequential, event-based, and object-oriented programming. Students will also work towards writing code that integrates multiple input/output modes. Programming style, multi-person programming projects, and debugging strategies will be covered as well. Uses the PYTHON language.

In addition to the regular class meeting there will be other group meetings.

This course is restricted to first-semester graduate students in the School of Information.

Graduate students will receive course credit, but because this is a lower-division course, the credit may not be applied toward the master's or doctoral degree unit requirements.

Upper-Division Courses

Instructor(s): Marti Hearst
Time: TuTh 2-3:30
Location: 210 South Hall
CCN: 42508

How to store, process, analyze and make sense of Big Data is of increasing interest and importance to technology companies, a wide range of industries, and academic institutions. In this course, UC Berkeley professors and Twitter engineers will lecture on the most cutting-edge algorithms and software tools for data analytics as applied to Twitter microblog data. Topics will include applied natural language processing algorithms such as sentiment analysis, large scale anomaly detection, real-time search, information diffusion and outbreak detection, trend detection in social streams, recommendation algorithms, and advanced frameworks for distributed computing. Social science perspectives on analyzing social media will also be covered.

This is a hands-on project course in which students are expected to form teams to complete intensive programming and analytics projects using the real-world example of Twitter data and code bases. Engineers from Twitter will help advise student projects, and students will have the option of presenting their final project presentations to an audience of engineers at the headquarters of Twitter in San Francisco (in addition to on campus). Project topics include building on existing infrastructure tools, building Twitter apps, and analyzing Twitter data. Access to data will be provided.

Intended audience:
This course is intended for students, both graduate and undergraduate, with programming skills and an interest in analyzing data and/or building software to do so.

Prerequisites:
Undergraduates must be upper-division computer science or electrical engineering majors, or must have taken significant advanced programming courses including CS 162 and math courses including CS 70 or equivalent. Completion of a statistics course is also strongly recommended.

Graduate students must be comfortable with systems programming and be able to pick up new software programming tools with little structured support and be comfortable with basic math topics such as graph theory, statistics, and probability theory.

NOTE: This course is also offered as Info 290. Analyzing Big Data with Twitter.

Core Courses

Instructor(s): Robert Glushko
Time: TuTh 9:30-11 (DIS Sec. 1 Tu 11-12, DIS Sec. 2 M 12-1 and DIS Sec. 3 M 1-2, Room 107)
Location: 166 Barrows
CCN: 42569

Three hours of lecture per week. This course introduces the intellectual foundations of information organization and retrieval: conceptual modeling, semantic representation, vocabulary and metadata design, classification, and standardization, as well as information organization and retrieval practices, technology, and applications, including computational processes for analyzing information in both textual and non-textual formats. Students will learn how information organization and retrieval is carried out by professionals, authors, and users; by individuals in association with other individuals, and as part of the business processes in an enterprise and across enterprises.

This is a required introductory course for MIMS Master's students, integrating perspectives and best practices from a wide range of disciplines.

Instructor(s): Deirdre Mulligan
Time: M 10-12 (DIS Sec. 1 Wed. 10-11, DIS Sec. 2 Wed. 11-12 in Room 210 South Hall
Location: 170 Barrows
CCN: 42581

Three hours of lecture per week. Law is one of a number of policies that mediates the tension between free flow and restrictions on the flow of information. This course introduces students to copyright and other forms of legal protection for databases, licensing of information, consumer protection, liability for insecure systems and defective information, privacy, and national and international information policy.

NOTE: Before Fall 2010, this course was offered for 2 units.

General Courses

Instructor(s): Tapan Parikh
Time: TuTh 11-12:30
Location: 210 South Hall
CCN: 42806

Three hours of lecture per week. User interface design and human-computer interaction. Examination of alternative design. Tools and methods for design and development. Human- computer interaction. Methods for measuring and evaluating interface quality.

This course covers the design, prototyping, and evaluation of user interfaces to computers which is often called Human-Computer Interaction (HCI). It is loosely based on course CS1 described in the ACM SIGCHI Curricula for Human-Computer Interaction (Association for Computing Machinery, 1992).

HCI covers many topics including:

  1. Human capabilities (e.g., visual and auditory perception, memory, mental models, and interface metaphors);
  2. Interface technology (e.g., input and output devices, interaction styles, and common interface paradigms); and,
  3. Interface design methods (e.g., user-centered design, prototyping, and design principles and rules), and interface evaluation (e.g., software logging, user observation, benchmarks and experiments).

This material is covered through lectures, reading, discussions, homework assignments, and a course project. This course differs from CS 160 primarily in two ways:

  1. There is an emphasis on interfaces for information technology applications; and,
  2. There is less emphasis on programming and system development, although some simple prototyping (for example, in visual basic or using JAVA GUI development tools) may be required. (CS 160 has a big programming project.)
Instructor(s): Doug Tygar
Time: MW 2-3:30
Location: 205 South Hall
CCN: 42587
This course will survey results in computer security, cryptography, and privacy, with an emphasis on work done in the last 3 years. Student projects (creative work, demonstrations, or literature reviews) will form a substantial portion of the course work. Prerequisite: IS 206 (Distributed Systems) or a strong background in distributed systems.
Instructor(s): Brian Carver
Time: MW 10:30- 12
Location: 202 South Hall
CCN: 42596

Three hours of lecture per week. This course will provide an overview of the intellectual property laws with which information managers need to be familiar. It will start with a consideration of trade secrecy law that information technology and other firms routinely use to protect commercially valuable information. It will then consider the role that copyright law plays in the legal protection of information products and services. Although patents for many years rarely were available to protect information innovations, patents on such innovations are becoming increasingly common. As a consequence, it is necessary to consider standards of patentability and the scope of protection that patent affords to innovators. Trademark law allows firms to protect words or symbols used to identify their goods or services and to distinguish them from the goods and services of other producers. It offers significant protection to producers of information products and services. Because so many firms license intellectual property rights, some coverage of licensing issues is also important. Much of the course will concern the legal protection of computer software and databases, but it will also explore some intellectual property issues arising in cyberspace.

Instructor(s): Staff
Time: TuTh 9-10:30
Location: 210 South Hall
CCN: 42599

Three hours of lecture. The Extensible Markup Language (XML), with its ability to define formal structural and semantic definitions for metadata and information models, is the key enabling technology for information services and document-centric business models that use the Internet and its family of protocols. This course introduces XML syntax, transformations, schema languages, and the querying of XML databases. It balances conceptual topics with practical skills for designing, implementing, and handling conceptual models as XML schemas.

Instructor(s): Staff
Time: TuTh 2-3:30
Location: 107 South Hall
CCN: 42602

This course is a survey of Web technologies, ranging from the basic technologies underlying the Web (URI, HTTP, HTML) to more advanced technologies being  used in the the context of Web engineering, for example structured data  formats and Web programming frameworks. The goal of this course is to provide an  overview of the technical issues surrounding the Web today, and to provide a  solid and comprehensive perspective of the Web's constantly evolving landscape.

Students will receive no credit for 253 after taking 290. Web Architecture.

Instructor(s): Ray Larson
Time: TuTh 12:30-2
Location: 202 South Hall
CCN: 42605

Three hours of lecture per week. This course is concerned with the use of Database Management Systems (DBMS) to solve a wide range of information storage, management and retrieval problems, in organizations ranging from large corporations to personal applications, such as research data management. The course combines the practical aspects of DBMS use with more theoretical discussions of database design methodologies and the "internals" of database systems.

A significant part of the course will require students to design their own database and implement it on different DBMS that run on different computer systems. We will use both ACCESS and ORACLE.

In the theoretical portion of the course, we will examine the major types or data models of DBMS (hierarchical, network, relational, and object-oriented). We will discuss the principles and problems of database design, operation, and maintenance for each data model.

Instructor(s): Coye Cheshire
Time: TuTh 3:30-5
Location: 210 South Hall
CCN: 42608

The goal of this course is to provide students with an introduction to many different types of quantitative research methods and statistical techniques. This course will be divided into two sections: 1) methods for quantitative research and, 2) quantitative statistical techniques for analyzing data. We begin with a focus on defining research problems, theory testing, causal inference, and designing research instruments. Then, we will explore a range of statistical techniques and methods that are available for empirical research. Topics in research methods include: Primary and Secondary Data Analysis, Sampling, Survey Design, and Experimental Designs. Topics in quantitative techniques include: Descriptive and Inferential statistics, General Linear Models, and Non-Linear Models. The course will conclude with an introduction to special topics in quantitative research methods.

Instructor(s): Jenna Burrell
Time: TuTh 12:30-2
Location: 205 South Hall
CCN: 42611

This course will focus upon the use of qualitative methods for research about information technologies. Methods including interviewing, focus groups, participant observation and ethnography will be taught and practiced. Significant qualitative research findings about the social impact of information technologies will be read, to analyze what we know about IT thus far, how we know it, and as models of theories and methods for future research. Frequent field exercises will be assigned to develop qualitative research skills and best practices, but the primary assignment will be to engage in a substantial fieldwork project. Methods covered will include video if grant support or other budget resources are found.

Instructor(s):
Time: M 2-5
Location: 107 South Hall
CCN: 42614

This seminar reviews current literature and debates regarding Information and Communication Technologies and Development (ICTD). This is an interdisciplinary and practice-oriented field that draws on insights from economics, sociology, engineering, computer science, management, public health, etc. Also listed as Energy and Resources Group C283.

Special Topics Courses

Instructor(s): Marti Hearst
Time: TuTh 2-3:30
Location: 210 South Hall
CCN: 42620

How to store, process, analyze and make sense of Big Data is of increasing interest and importance to technology companies, a wide range of industries, and academic institutions. In this course, UC Berkeley professors and Twitter engineers will lecture on the most cutting-edge algorithms and software tools for data analytics as applied to Twitter microblog data. Topics will include applied natural language processing algorithms such as sentiment analysis, large scale anomaly detection, real-time search, information diffusion and outbreak detection, trend detection in social streams, recommendation algorithms, and advanced frameworks for distributed computing. Social science perspectives on analyzing social media will also be covered.

This is a hands-on project course in which students are expected to form teams to complete intensive programming and analytics projects using the real-world example of Twitter data and code bases. Engineers from Twitter will help advise student projects, and students will have the option of presenting their final project presentations to an audience of engineers at the headquarters of Twitter in San Francisco (in addition to on campus). Project topics include building on existing infrastructure tools, building Twitter apps, and analyzing Twitter data. Access to data will be provided.

Intended audience:
This course is intended for students, both graduate and undergraduate, with programming skills and an interest in analyzing data and/or building software to do so.

Prerequisites:
Undergraduates must be upper-division computer science or electrical engineering majors, or must have taken significant advanced programming courses including CS 162 and math courses including CS 70 or equivalent. Completion of a statistics course is also strongly recommended.

Graduate students must be comfortable with systems programming and be able to pick up new software programming tools with little structured support and be comfortable with basic math topics such as graph theory, statistics, and probability theory.

NOTE: This course is also offered as Info 190. Analyzing Big Data with Twitter.

290. Multimedia Narrative (Sec 2) (3 units)
Instructor(s): Nancy Van House
Time: TuTh 11-12:30
Location: 205 South Hall
CCN: 42623

Visual and multi-modal media are central to much of what we do in the I School and related disciplines. Data collection, reports, and presentations, face-to-face and distant, online and off, often rely heavily on visual and audio media. Because we are a media-literate society, with accessible hardware and software plus easy online distribution, it seems that everyone “knows" how to make and critique such media. However, our knowledge about how to effectively make, use, and present these media trails far behind our ability to create hours and gigabytes of content. Furthermore, it’s useful to consider how these resources are changing not just professional and research practice.

In this seminar, we will address both theoretical and practical issues of capturing and creating narratives with video, audio, and still images. We will draw on photojournalism, visual narrative, visual anthropology, visual studies, and related areas. We will get hands-on experience creating and editing our own media. This is not a technical course; nor is it a media production how-to. But you will get experience with media technologies while we reflect on them with the help of theoreticians and scholars in relevant areas.

This course is relevant to students in professional schools and to doctoral students interested in and qualitative research, including user experience research; technology designers who produce video scenarios and concept videos; and anyone concerned with collecting and presenting information via multiple media.

No prior experience is necessary, but students who are already grappling with visual (and audio) media will find this course especially useful. I School students are likely to find this course useful for the doing and presenting of final projects.

290. ICTD Research Seminar (Sec 10) (1 units)
Instructor(s): Tapan Parikh
Time: Th 2-3
Location: 205 South Hall
CCN: 42638

The ICTD group seminar will discuss topics of current interest in the emerging multidisciplinary field of Information and Communications Technologies and Development, or ICTD. Each semester will be focused on a particular topic or set of topics, under the direction of appropriate faculty from the I School's ICTD group. The course content will consist of paper discussions, invited lectures from both within and outside the class and a some relatively short written assignments. Students will also be responsible for presenting during at least on class session, either on their own research, ideas or on a selected set of papers relevant to the semester's chosen topic.

Note: This course is being offered on a S/U (Satisfactory/Unsatisfactory) basis.

Instructor(s): Quentin Hardy
Time: M 3:30-6:30 (August 27 - October 1)
Location: 210 South Hall
CCN: 42641

Mass communications technologies have been profound influencers of human identity, from the printing press and the rise of vernacular political cultures to television and the power of celebrity. While the Web is still a work in progress, salient characteristics such as the collapse of distance, the discovery of like-minded groups, and information delivered in short bursts are already affecting the way people see themselves and the way they consume information. Following an overview on the relationship of technology with identity and communications, the course will look at the uses of narrative in news, public relations, advertising, entertainment, and online gaming.

Instructor(s): Scott Young
Time: F 1-3 (Sept. 7 - Oct. 26)
Location: 202 South Hall
CCN: 42644

Health and health care have profound impact on a society's well being and economic productivity. Health care reform and ongoing economic forces are placing unprecedented pressure on the health care system to provide consumers and payers with value. Patients, purchasers, regulators, and other key stakeholders are demanding that care be readily accessible, proactive, and focused on improving health while containing costs. The health care system, policy makers, and key stakeholders are responding by developing new care models that focus on patient and customer centricity, novel information practices, and the seamless integration of care.

Following a review of the current trends in health care, the course will explore the relationship between health care and the information economy. We will also delve into information strategies being utilized by health care providers, patients, payers, and other key stakeholders to improve care while controlling costs. Health care leaders from Kaiser Permanente will serve as guest lecturers, providing tangible perspective to our discussions.

290A. Social Data Revolution (Sec 3) (1 units)
Instructor(s): Andreas Weigend
Time: M 3:30-6:30 (August 27 - October 1)
Location: 202 South Hall
CCN: 42646

Free communication has changed the world, including the expectations and work and play. The class begins with the two data revolutions--the first about passively collected clicks on the web, the second about actively contributed data, as platforms like Facebook empower individuals to contribute a variety of quantitative and qualitative data (transactions, social relations, attention gestures, intention, location, and more.) With active student participation, we explore the far-reaching implications of the consumer data revolution for individuals, communities, business, and society.

Instructor(s): Anne Walker
Time: Th 6-8
Location: 210 South Hall
CCN: 42647

It takes critical thinking, outstanding leadership, and a little magic to be a successful project manager. Come and learn not only the essential building blocks of project management, but the tricks to managing a variety of complex projects. We will have a combination of interactive lectures, guest speakers, and case studies discussions to  cover globally recognized standards, best practices and tools that successful project managers use.

This course satisfies the Management requirement for the MIMS degree.

Students will receive no credit for 290MA after taking 290. Effective Project Management.

Instructor(s): Staff
Time: TuTh 3:30-5
Location: 202 South Hall
CCN: 42650

Students will build tools to explore and apply theories of information organization and retrieval. Students will implement various concepts covered in the concurrent 202 course through small projects on topics like controlled vocabularies, the semantic web, and corpus analysis. We will also experiment with topics suggested by students during the course. Students will develop skills in rapid prototyping of web-based projects using Python, XML, and jQuery.

This course satisfies the technology requirement for the MIMS degree.

Students will receive no credit for 290TA after taking 290. Information Organization Lab.

Seminar Courses

Instructor(s): Jenna Burrell
Time: M 12:30-2
Location: 205 South Hall
CCN: 42656

One hour colloquium per week. Must be taken on a satisfactory/unsatisfactory basis. Colloquia, discussion, and readings are designed to introduce students to the range of interests of the school.

296A. Information Access (Sec 1) (3 units)
Time: F 3-5
Location: 107 South Hall
CCN: 42659

The seminar explores selected advanced topics relating to 'digital libraries' with special emphasis on:

  • Access to networked resources
  • Use of two or more resources in conjunction
  • Combined use of two or more retrieval systems (e.g. use of pre- or post-processing to enhance the capabilities)
  • The redesign of library services

It is expected that these issues will require attention to a number of questions about the nature of information retrieval processes, the feasibility of not-yet-conventional techniques, techniques of making different systems work together, social impact, and the reconsideration of past practices. More generally, the seminar is intended to provide a forum for advanced students in the School. Anyone interested in these topics is welcome to join in -- and to talk about their own work. This is a continuation of the previous Lynch/Buckland seminars.

296A. Technology and Delegation (Sec 2) (2 units)
Instructor(s): Deirdre Mulligan
Time: M 3:30-5:30
Location: 205 South Hall
CCN: 42662

Information technology has been integrated into an array of complex interactions between individuals and the state. Often these technological changes are put forth as inevitable progress toward modernization and as value-neutral means for acting upon policies established through the political branch of government. However, the adoption or introduction of specific technology can obscure profound policy choices and options. Obscurity can arise due to barriers to transparency created by law, such as intellectual property rights asserted to prevent the analysis of software code used in electronic voting systems, due to a lack of necessary expertise to understand the ramifications of a technological shift within the public and private sector entities focused on the relevant policy issues, or, more fundamentally, due to shifts in technology that remove or shift the assumptions on which earlier policies were developed. As a result, the agency, the public, and the political branch of government may overlook the policy-implications in the choice of a new technology. Through case studies this class will explore existing examples where discretion has been delegated to, or embedded in technology, mechanisms that have or could be used to limit and manage this delegation, and techniques for early identification of inappropriate delegations.