Information Course Schedule Spring 2020

Surveying history through the lens of information and information through the lens of history, this course looks across time to consider what might distinguish ours as “the information age” and what that description implies about the role of “information technology” across time. We will select moments in societies’ development of information production, circulation, consumption, and storage from the earliest writing and numbering systems to the world of Social Media. In every instance, we’ll be concerned with what and when, but also with how and why. Throughout we will keep returning to questions about how information-technological developments affect society and vice versa?

Three hours of lecture per week. Methods and concepts of creating design requirements and evaluating prototypes and existing systems. Emphasis on computer-based systems, including mobile system and ubiquitous computing, but may be suitable for students interested in other domains of design for end-users. Includes quantitative and qualitative methods as applied to design, usually for short-term term studies intended to provide guidance for designers. Students will receive no credit for 114 after taking 214.

This course introduces students to natural language processing and exposes them to the variety of methods available for reasoning about text in computational systems. NLP is deeply interdisciplinary, drawing on both linguistics and computer science, and helps drive much contemporary work in text analysis (as used in computational social science, the digital humanities, and computational journalism). We will focus on major algorithms used in NLP for various applications (part-of-speech tagging, parsing, coreference resolution, machine translation) and on the linguistic phenomena those algorithms attempt to model. Students will implement algorithms and create linguistically annotated data on which those algorithms depend.

Introduces the data sciences landscape, with a particular focus on learning data science techniques to uncover and answer the questions students will encounter in industry. Lectures, readings, discussions, and assignments will teach how to apply disciplined, creative methods to ask better questions, gather data, interpret results, and convey findings to various audiences. The emphasis throughout is on making practical contributions to real decisions that organizations will and should make.

This course is designed to be an introduction to the topics and issues associated with information and information technology and its role in society. Throughout the semester we will consider both the consequence and impact of technologies on social groups and on social interaction and how society defines and shapes the technologies that are produced. Students will be exposed to a broad range of applied and practical problems, theoretical issues, as well as methods used in social scientific analysis. The four sections of the course are: 1) theories of technology in society, 2) information technology in workplaces 3) automation vs. humans, and 4) networked sociability.

This course uses examples from various commercial domains — retail, health, credit, entertainment, social media, and biosensing/quantified self — to explore legal and ethical issues including freedom of expression, privacy, research ethics, consumer protection, information and cybersecurity, and copyright. The class emphasizes how existing legal and policy frameworks constrain, inform, and enable the architecture, interfaces, data practices, and consumer facing policies and documentation of such offerings; and, fosters reflection on the ethical impact of information and communication technologies and the role of information professionals in legal and ethical work.

This course addresses concepts and methods of user experience research, from understanding and identifying needs, to evaluating concepts and designs, to assessing the usability of products and solutions. We emphasize methods of collecting and interpreting qualitative data about user activities, working both individually and in teams, and translating them into design decisions. Students gain hands-on practice with observation, interview, survey, focus groups, and expert review. Team activities and group work are required during class and for most assignments. Additional topics include research in enterprise, consulting, and startup organizations, lean/agile techniques, mobile research approaches, and strategies for communicating findings.

Three hours of lecture per week. Prerequisites: Graduate standing. As it's generally used, "information" is a collection of notions, rather than a single coherent concept. In this course, we'll examine conceptions of information based in information theory, philosophy, social science, economics, and history. Issues include: How compatible are these conceptions; can we talk about "information" in the abstract? What work do these various notions play in discussions of literacy, intellectual property, advertising, and the political process? And where does this leave "information studies" and "the information society"?

Discusses application of social psychological theory and research to information technologies and systems; we focus on sociological social psychology, which largely focuses on group processes, networks, and interpersonal relationships. Information technologies considered include software systems used on the internet such as social networks, email, and social games, as well as specific hardware technologies such as mobile devices, computers, wearables, and virtual/augmented reality devices. We examine human communication practices, through the lens of different social psychology theories, including: symbolic interaction, identity theories, social exchange theory, status construction theory, and social networks and social structure theory.

The design and presentation of digital information. Use of graphics, animation, sound, visualization software, and hypermedia in presenting information to the user. Methods of presenting complex information to enhance comprehension and analysis. Incorporation of visualization techniques into human-computer interfaces. Three hours of lecture and one hour of laboratory per week.

Provides a theoretical and practical introduction to modern techniques in applied machine learning. Covers key concepts in supervised and unsupervised machine learning, including the design of machine learning experiments, algorithms for prediction and inference, optimization, and evaluation. Students will learn functional, procedural, and statistical programming techniques for working with real-world data.

This course is a survey of web technologies that are used to build back-end systems that enable rich web applications. Utilizing technologies such as Python, Flask, Docker, RDBMS/NoSQL databases, and Spark, this class aims to cover the foundational concepts that drive the web today. This class focuses on building APIs using micro-services that power everything from content management systems to data engineering pipelines that provide insights by processing large amounts of data. The goal of this course is to provide an overview of the technical issues surrounding back-end systems today, and to provide a solid and comprehensive perspective of the web’s constantly evolving landscape.

Three hours of lecture per week. Introduction to relational, hierarchical, network, and object-oriented database management systems. Database design concepts, query languages for database applications (such as SQL), concurrency control, recovery techniques, database security. Issues in the management of databases. Use of report writers, application generators, high level interface generators.

This course introduces students to natural language processing and exposes them to the variety of methods available for reasoning about text in computational systems. NLP is deeply interdisciplinary, drawing on both linguistics and computer science, and helps drive much contemporary work in text analysis (as used in computational social science, the digital humanities, and computational journalism). We will focus on major algorithms used in NLP for various applications (part-of-speech tagging, parsing, coreference resolution, machine translation) and on the linguistic phenomena those algorithms attempt to model. Students will implement algorithms and create linguistically annotated data on which those algorithms depend.

This course covers computational approaches to the task of modeling learning and improving outcomes in Intelligent Tutoring Systems (ITS) and Massive Open Online Courses (MOOCs). We will cover theories and methodologies underpinning current approaches to knowledge discovery and data mining in education and survey the latest developments in the broad field of human learning research. The course is project based; teams will be introduced to online learning platforms and their datasets with the objective of pairing data analysis with theory or implementation. Literature review will add context and grounding to projects.

This course will cover new interface metaphors beyond desktops (e.g., for mobile devices, computationally enhanced environments, tangible user interfaces) but will also cover visual design basics (e.g., color, layout, typography, iconography) so that we have systematic and critical understanding of aesthetically engaging interfaces. Students will get a hands-on learning experience on these topics through course projects, design critiques, and discussion, in addition to lectures and readings. Two hours of lecture per week.

Civil society and governments across the world continue to push social media platforms for increased responsiveness to concerns about the abuse of technology. Recent nationally representative surveys reveal a widening trust deficit between the public and private technology companies. This has led to a growing job market for technology policy professionals that can help companies navigate complex issues related to online hate and harassment, and for engineers who understand user-needs for vulnerable communities. This course will provide an opportunity for UC Berkeley graduate students to engage in lectures and guided design exercises aimed at improving the affordances of social media platforms with regard to civil and respectful discourse.

This course provides students with real-world experience assisting politically vulnerable organizations and persons around the world to develop and implement sound cybersecurity practices. In the classroom, students study basic theories and practices of digital security, intricacies of protecting largely under-resourced organizations, and tools needed to manage risk in complex political, sociological, legal, and ethical contexts. In the clinic, students work in teams supervised by Clinic staff to provide direct cybersecurity assistance to civil society organizations. We emphasize pragmatic, workable solutions that take into account the unique needs of each partner organization.

In this group study class, we will cover the material in Data 8 using the online Data 8X a three-part professional certificate program in data science from UC Berkeley. This first course, “Computational Thinking with Python,” focuses on programming and data visualization. The second course, “Inferential Thinking by Resampling,” will focus on statistical inference. The third course is “Prediction and Machine Learning.”

This group study is intended for graduate students in professional schools who seek an introduction to data science in order to integrate techniques into their domain or to pursue further educational opportunities such as the graduate certificate in applied data science. The class format is essentially self-guided: students will watch the video lecture and complete the assignments before class, and then meet to discuss the lesson. Undergraduate assistants from Data 8 will coach class participants as necessary. There are small class projects that allow students to work with their own datasets.

Data 8X is based on a rigorous first-year undergraduate course at UC Berkeley called Foundations of Data Science. Over 1,000 students take this course each semester. The course is designed as an introduction to programming and statistics for students from many different majors. It teaches practical techniques that apply across many disciplines, and also serves as the technical foundation for more advanced courses in data science, statistics, and computer science.

No prior programming experience is necessary, but many of the programming techniques covered in this course do not appear in a typical introduction to programming. The programming content of this course focuses on manipulating data tables, rather than building software applications. Therefore, students who take the course after taking other programming courses often learn a new approach to programming that they haven't encountered before.

The Advanced Citizen Clinic practicum is for students who have already completed Info 289. Public Interest Cybersecurity: The Citizen Clinic Practicum.

For individuals and organizations involved in political advocacy, cybersecurity threats are an increasingly common reality of operating in the digital world. Civil society has always been under attack from ideological, political, and governmental opponents who seek to silence dissenting opinions, but the widespread adoption of connected technologies by the individuals and organizations that make up civil society creates a new class of vulnerabilities. Citizen Clinic at the Center for Long-Term Cybersecurity provides students with real-world experience assisting politically vulnerable organizations and persons around the world to develop and implement sound cybersecurity practices.

Advanced students will spend the majority of their credit hours engaging directly with clients under the supervision of Clinic staff. Emphasis will be on advanced threat research and security mitigations. Enrollment will be by application only. Eligible students will be placed on the waitlist and then contacted with instructions to apply for admission to the course.

Privacy counseling and compliance is a rapidly growing and increasingly important function, both within companies and throughout the legal profession. The task is becoming evermore complex as companies grapple with adherence to new legislation and regulation, as well as local and international standards and norms. This interdisciplinary course seeks to help prepare students for this changing ethical, legal, and regulatory landscape. The academic perspective will be grounded in a real world examination of compliance challenges which will be presented by leading privacy professionals including in-house legal and compliance experts.

The Future of Cybersecurity Reading Group (FCRG) is a two-credit discussion seminar focused on cybersecurity. In the seminar, graduate, professional, and undergraduate students discuss current cybersecurity scholarship, notable cybersecurity books, developments in the science of security, and evolving thinking in how cybersecurity relates to political science, law, economics, military, and intelligence gathering. Students are required to participate in weekly sessions, present short papers on the readings, and write response pieces. The goals of the FCRG are to provide a forum for students from different disciplinary perspectives to deepen their understanding of cybersecurity and to foster and workshop scholarship on cybersecurity.

This course is a graduate-level introduction to HCI research. Students will learn to conduct original HCI research by reading and discussing research papers while collaborating on a semester-long research project. The class will focus on both the positive potentials of technology as well as the negative consequences that new technologies may have on society. Each week the class will focus on a theme of HCI research and review foundational, cutting-edge, and critical theory research relevant to that theme.

This is a research-oriented graduate class on human-centered aspects in data management and analysis across the end-to-end data science/AI lifecycle. The class will entail reading and discussion of classical and modern research papers in this space. As part of this class, students will undertake a research project in this space. Students taking the class should have taken a database or data engineering class, at the level of INFO 258 / DATA 101 / COMPSCI 186, and/or have experience working with database or data engineering tools.

In this course you’ll learn industry-standard agile and lean software development techniques such as test-driven development, refactoring, pair programming, and specification through example. You’ll also learn good object-oriented programming style. We’ll cover the theory and principles behind agile engineering practices, such as continuous integration and continuous delivery.

This class will be taught in a flip-the-classroom format, with students programming in class. We'll use the Java programming language. Students need not be expert programmers, but should be enthusiastic about learning to program. Please come to class with laptops, and install IntelliJ IDEA community edition. Students signing up should be comfortable writing simple programs in Java (or a Java-like language such as C#).

An intensive weekly discussion of current and ongoing research by Ph.D. students with a research interest in issues of information (social, legal, technical, theoretical, etc.). Our goal is to focus on critiquing research problems, theories, and methodologies from multiple perspectives so that we can produce high-quality, publishable work in the interdisciplinary area of information research. Circulated material may include dissertation chapters, qualifying papers, article drafts, and/or new project ideas. We want to have critical and productive discussion, but above all else we want to make our work better: more interesting, more accessible, more rigorous, more theoretically grounded, and more like the stuff we enjoy reading.

One hour colloquium per week. Must be taken on a satisfactory/unsatisfactory basis. Prerequisites: Ph.D. standing in the School of Information. Colloquia, discussion, and readings designed to introduce students to the range of interests of the school.

Topics in information management and systems and related fields. Specific topics vary from year to year. May be repeated for credit, with change of content. May be offered as a two semester sequence.