- INFO 1101 - Computation in Society
- INFO 1111 - Intro to Information Science: Understanding the World Through Data
- INFO 1201 - Computational Reasoning 1
- INFO 2001/4001 - Information Science Portfolio and Professional Development
- INFO 2131 - Information Ecosystems
- INFO 3401 - Information Exploration
- INFO 3501/5501 - Online Collaboration
- INFO 3505/5505 - Designing for Creativity and Learning
- INFO 3506 - Online Fandom
- INFO 4604 - Applied Machine Learning
- INF 4606/5606 - Critical Technical Practice
- INFO 6301 - Computation for Research in Information Science
- INFO 6500 - Information Science Seminar
- INFO 7000 - Intro to Doctoral Studies in Information Science
Dr. William Aspray
Lecture: TuTh 8:00am - 9:15am, MUEN E050
Introduces students to modern information and communication technology, the basic principles of software and programming, the fundamental role of algorithms in modern society, computational reasoning, the major organizations in the information sector and fundamental interactions between humans and information technology.
Though students are encouraged to alternately take INFO1201 if they are interested in getting a start at becoming a producer as well as a consumer of information technology, this course provides students with a foundational understanding of technology in a societal context. It will also devote two weeks to giving students brief experience with programming, and practical skills such as working with spreadsheets.
The instructor has training in both history and social science, and this course will go beyond technology and place it in a historical and social context.
Dr. Jed Brubaker
Seminar: TuTh, 11am - 12:15pm
Studio: Wednesdays, variable
Everyone works with data. In this course, you’ll learn how to make data work for you.
Through hands-on explorations, activities, and small group projects, students will learn how to capture, transform, and represent data. Guided by the Information Science Lifecycle, students will learn how to identify problems, ask researchable questions, collect and analyze information, present their findings, and make an impact on real world problems.
By the end of this course, students will have experience working with multiple forms of data — including interview, survey, and big data — and know how to present their findings in visual and interactive formats.
Lecture: MWF 10:00am - 10:50am, HLMS 252
Lab: Mondays, variable
OR
Lecture: MWF 2:00pm - 2:50pm, EKLC E1B20
Lab: Wednesdays, variable
Computing and information technologies permeate all aspects of our lives. They inspire how we connect with each other online through social networks and how we find information through search engines. Technologies also drive our physical world in how we navigate transportation systems and how we manage money on banking applications. Everyone should have the ability to not only use and interact with computing, but to also create and express themselves with computing.
This course is a hands-on introduction to create, invent, and build with computer programming. No programming experience is necessary and all backgrounds are welcome. Students will become exposed to high-level computational concepts and practices that include algorithms, data, parallelism, abstraction, and debugging. Assignments and projects will involve learning to program using the Scratch and Python programming languages. The creative and problem-solving strategies introduced in this course are applicable across many domains beyond information and computer sciences.
How do you present your personal "brand" online, on the phone, in teleconferernce, or in person? Portfolio and Professional Development helps students successfully present themselves and describe their expertise for meeting career goals. The course is taken by lower and upper division students, which allows for a tiered mentoring approach as students practice a variety of skills and learn from guest speakers.
Dr. Lecia Barker
Lecture: TuTh 3:30pm - 4:45pm, EDUC 220
In Fall 2018, we will take a walk through the Smart City, exploring how the urban environments of the future are shaped by how we produce, understand, use, and misuse information. We will begin the semester by learning theoretical frameworks for information ecosystems as related to communities, organizations, and institutions. We will apply these theories to the the example of Smart Cities. Students will learn about and engage in participant observation, digital ethnography, and other methods of understanding information behavior in cultural-spatial contexts.
Dr. Danielle Szafir
Lecture: MWF 2:00pm - 2:50pm, HUMN 1B90
Teaches students how to use information to identify interesting real world problems and to generate insight. Students will learn to find, collect, assemble and organize data to inspire new questions, make predictions, generate deliverables, and work towards solutions. They will learn to appropriately apply different methods (including computational, statistical and qualitative) for exploratory data analysis in a variety of domains.
Pre-requisites: INFO 2201 and INFO 2301 and INFO 1111 or INFO 1121 (all minimum grade C-). Restricted to students with 57 or more hours.
Dr. Brian Keegan
Lecture: TuTh 5:00pm - 6:15pm, DUAN G2B47
Analyzes the mechanisms of peer production and crowdsourcing systems like Wikipedia and OpenStreetMap. Students will investigate how these crowdsourced platforms work socially and technically, develop skills using tools for their analysis and critically evaluate platform and community limitations.
Pre-requisites: Restricted to students with 57 or more hours.
Dr. Ricarose Roque
Studio: TuTh 9:30am - 10:45am, HALE 260
How can we engage and inspire people to play, invent, and express themselves with technology?
This course analyzes learning technologies, discusses learning theories, and develops prototypes of technologies, activities, and environments to investigate how to engage people in creative and inclusive learning experiences. Students will examine systems like construction kits for kids, online learning communities, and makerspaces with a critical lens on equity and inclusion. The course’s studio format enables students to apply constructionist ideas into the design of technology-enabled experiences.
Pre-requisites: Restricted to students with 57 or more hours.
Dr. Casey Fiesler Lecture: TuTh 2:00pm - 3:15pm, HLMS 211
Explores and analyzes fan communities in a digital context. Through applied research, students will investigate online spaces devoted to participatory and remix culture, media fandom, and fan creation. This class will draw concepts and methods from fan studies, social computing, ethnography, data science, and sociology to drive project-based inquiry.
Pre-requisites: Restricted to students with 57 or more hours.
Dr. Michael Paul
Lecture: TuTh 3:30pm - 4:45pm, DUAN G125
Introduces algorithms and tools for building intelligent computational systems. Methods will be surveyed for classification, regression, and clustering in the context of applications such as document filtering and image recognition. Students will learn the theoretical underpinnings of common algorithms (drawing from mathematical disciplines including statistics and optimization) as well as the skills to apply machine learning in practice.
Pre-requisites: Requires prerequisite courses of INFO 2201 or INFO 2301 or CSCI 2270 (all minimum grade C-). Restricted to students with 57 or more hours.
Dr. Laura Devendorf
Lecture: MW 3:00pm - 4:15pm, ATLS 1B31
Surveys design theory and methods that can be used to question relationships between technology, culture, and the environment. Students will discuss readings and synthesize those readings through design exercises. The course will equip students with resources for thinking more critically and creatively about technology and how design can shape human-technology relationships in the future.
Cross-listed with ATLS4606/5606.
INFO 5606 / ATLS 5606 restricted to graduate students only.
Dr. Stephen Voida
Lecture: TuTh 12:30pm - 1:45pm, HUMN 335
Introduces principles of computational thinking through the manipulation, transformation, and creation of data artifacts used in research. Students will be exposed to a high-level overview of algorithms, functions, data structures, recursion, and object-oriented computer programming through a series of assignments that emphasize the use of computation as a means of scholarship.
Enrollment restricted to graduate INFO students, or with instructor permission.
Dr. Leysia Palen
Seminar: Wed 2:00pm - 2:50pm
Enculturates graduate students in the discipline of Information Science through weekly seminar series that hosts guest speakers, internal faculty and graduate speakers and other community building and professional development activities.
Enrollment restricted to graduate INFO students, or with instructor permission.
Dr. Leysia Palen
Seminar: Friday 11:00am - 1:30pm
Introduces students to practices associated with successful advancement in a doctoral program, rigorous scholarship in information science and more expert and early participation in their scholarly community of practice.
Restricted to Information Science (INFO) Ph.D. graduate students only.
Need help or have questions?
View the CMCI advising page for more information, or contact the academic advisor for Information Science:
Grace A. Johnson
Academic Advisor
Walk-in Hours and Appointments: MyCUHub
grace.johnson@colorado.edu
Voicemail: (email preferred) 303-492-1835
Stadium 110F