Info 190

Special Topics in Information

1-3 units

Course Description

Specific topics, hours and credit may vary from section to section, year to year. May be repeated for credit with change in content.



Courses Offered

Specific topics, hours and credit may vary from section to section, year to year. May be repeated for credit with change in content.

(Description unavailable)

This course introduces students to practical fundamentals of data mining and machine learning with just enough theory to aid intuition building. The course is project-oriented, with a project beginning in class every week and to be completed outside of class by the following week, or two weeks for longer assignments. The in-class portion of the project is meant to be collaborative, with the instructor working closely with groups to understand the learning objectives and help them work through any logistics that may be slowing them down. Weekly lectures introduce the concepts and algorithms which will be used in the upcoming project. Students leave the class with hands-on data mining and data engineering skills they can confidently apply.

A seminar focusing on topics of current interest. Topics will vary. A seminar paper will be required. Open to students from other departments.

From criminal justice to health care to municipal services, civic technology is transforming the public sector. Taught by experts from the California Department of Justice, this course explores the emerging disciplines of data science, digital services, and user­-centered design and their implications for government and public policy.

This course aims to provide students with an overview of the many dynamic and interdisciplinary skills that are required for successful practice in the field of ICTD.

Information and Communications Technology for Development (ICTD) is the broad study of information technology to alleviate poverty and stimulate development (economic, social, and human) in developing and transitional countries. In the last 15 years, there has been an exponential expansion in the number of ICTD projects, but insufficient human skills to design and manage them, leading to a “forever-pilot” culture and a rather dismal failure rate. Successful oversight of these projects requires a combination of interdisciplinary and dynamic skills. This course serves to introduce students to these skills under three areas of competencies:

A. Contextual: Broader conceptual, policy-level frameworks of understanding the landscape of ICTD.

B. Technical: The different ways in which ICTs, through e-applications, can contribute to socioeconomic development. While specific computer skills are important, this course given its broad reach will focus on applications.

C. Management: Methods and techniques of project program planning and management, including assessment, design, funding, implementation, and evaluation.

Along with these areas, we will explore cross-cutting themes such as politics, gender, culture, and the reality of development work.

Students will be introduced to these skills through lectures and discussions (face-to face and online), as well as application to cases (possibly live consulting cases). Expect to have a lot of fun while working hard — not unlike development work in real life!

Three hours of lecture per week. Application of economic tools and principles, including game theory, industrial organization, information economics, and behavioral economics, to analyze business strategies and public policy issues surrounding information technologies and IT industries. Topics include: economics of information; economics of information goods, services, and platforms; strategic pricing; strategic complements and substitutes; competition models; network industry structure and telecommunications regulation; search and the "long tail"; network cascades and social epidemics; network formation and network structure; peer production and crowdsourcing; interdependent security and privacy.

This course introduces students to data visualization: the use of the visual channel for gaining insight with data, exploring data, and as a way to communicate insights, observations, and results with other people.

The field of information visualization is flourishing today, with beautiful designs and applications ranging from journalism to marketing to data science. This course will introduce foundational principles and relevant perceptual properties to help students become discerning judges of data displayed visually. The course will also introduce key practical techniques and include extensive hands-on exercises to enable students to become skilled at telling stories with data using modern information visualization tools.

Students will be asked to complete assignments before class, work together in small groups in class, and provide peer assessments. Grades will be based on assignments, quizzes, in class participation, peer assessment quality, 2 midterms, and a final project. The assignments for the course will together work towards building a coherent visualization that tells a story and is visible on the web.


This course is designed for upper division undergraduates who have an interest in design and in data. It is intended to accommodate students who have only a limited programming background, as well as those who are skilled with programming. For this reason, the only prerequisite is CS/Stat/Info 8 or equivalent. This course assumes students already have familiarity with basic data analysis and manipulation, and basic statistics.

Students are encouraged but not required to have taken other courses from the introductory design sequence (one of DES INV 10- Discovering Design DES INV 15- Design Methodology, DES INV 21- Visual Communications & Sketching, CS 160 User Interface Design and Development), as well as other introductory data science and statistics courses.

Graduate students will be accommodated only as space permits.

For Computer Science Students

Those students from Computer Science who would prefer a programming component, and who would like to receive technical course requirement credits for this course should enroll in a 1 unit optional companion course that is being offered alongside this course. This companion course will teach JavaScript and d3.js for information visualization applications.


The course instructor is Professor Marti Hearst, one of the founders of the IEEE Infovis Conference. She is also a leader in the latest wave of innovations in teaching data visualization, and co-organized high-profile events on this topic at IEEE Infoviz 2015, 2016, and 2017. Prof. Hearst is internationally known for her research in user interfaces for search and text visualization, having recently been inducted into the ACM CHI Academy.

This is a weekly one-hour seminar on the latest topics in the field of Natural Language Processing (also known as Computational Linguistics). Researchers from across UC Berkeley as well as visitors from out of town will present their recent work for discussion and feedback. Past topics have included multilingual language processing, analyzing social text, analyzing text using joint models, unsupervised morphology induction using word embeddings, deep learning of visual question answering, and unsupervised transcription of music and language.

In Fall 2016, we will meet every week, with alternating weeks consisting of discussions of readings and presentations of new research by local and visiting speakers.

Anyone is welcome to audit the course. Graduate students and undergraduates may enroll in this course for 1 unit of credit. In order to earn that unit of credit, students must write a synopsis of a research paper every two weeks, must attend at least 11 class meetings (and arrive on time), and must lead (or co-lead) at least one discussion of a research paper during the course of the semester.

Course may be repeated for credit. Three hours of lecture per week for five weeks.

This studio course introduces students to design thinking and the basic practices of interaction design. Following a human-centered design process that includes research, concept generation, prototyping, and refinement, students will work as individuals and in small teams to design mobile information systems and other interactive experiences. Assignments approach design on three levels: specific user interactions, contexts of use, and larger systems. Becoming familiar with design methodologies such as sketching, storyboarding, wire framing, and prototyping, students will learn core skills for understanding the rich contexts of stakeholders and their interactions with technology, for researching competing products and services, for modeling the current and preferred state of the world, and for prototyping and communicating possible solutions.

No coding is required.

Last updated:

September 2, 2016