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1 - 6 of 6 results for: COMM 273D

COMM 113: Computational Methods in the Civic Sphere (COMM 213)

The widespread availability of public data provides a rich opportunity for those who can efficiently filter, interpret, and visualize information. Course develops necessary technical skills for data collection, analysis, and publication, including data mining and web visualization, with a focus on civic affairs and government accountability. Open to all majors and a range of technical skill levels. Involves tackling new tools and technical concepts in the pursuit of engaging, public-facing projects. (Graduate students enroll in 213). Prerequisite COMM 273D, CS 106A, or CS 106B.
Terms: Win | Units: 4-5 | UG Reqs: GER:DB-EngrAppSci | Grading: Letter or Credit/No Credit
Instructors: Nguyen, D. (PI)

COMM 177A: Computational Journalism (COMM 277A)

Focuses on using data and algorithms to lower the cost of discovering stories or telling stories in more engaging and personalized ways. Project based assignments based on real-world challenges faced in newsrooms. Prior experience in journalism or computational thinking helpful. Prerequisite: Comm 273D, COMM 113/213, or the consent of instructor.
Terms: Spr | Units: 4 | Grading: Letter or Credit/No Credit
Instructors: Nguyen, D. (PI)

COMM 213: Computational Methods in the Civic Sphere (COMM 113)

The widespread availability of public data provides a rich opportunity for those who can efficiently filter, interpret, and visualize information. Course develops necessary technical skills for data collection, analysis, and publication, including data mining and web visualization, with a focus on civic affairs and government accountability. Open to all majors and a range of technical skill levels. Involves tackling new tools and technical concepts in the pursuit of engaging, public-facing projects. (Graduate students enroll in 213). Prerequisite COMM 273D, CS 106A, or CS 106B.
Terms: Win | Units: 4-5 | Grading: Letter or Credit/No Credit
Instructors: Nguyen, D. (PI)

COMM 273D: Public Affairs Data Journalism I

Even before the ubiquity of Internet access and high-powered computers, public accountability reporting relied on the concerted collection of observations and analytical problem-solving. We study the methods, and the data, used to discover leads and conduct in-depth reporting on public affairs, including election finance and safety regulations. Students gain practical experience with the digital tools and techniques of computer-assisted reporting. Prerequisite: Journalism M.A. student.
Terms: Aut | Units: 4 | Repeatable for credit | Grading: Letter or Credit/No Credit
Instructors: Nguyen, D. (PI)

COMM 274D: Public Affairs Data Journalism II

Learn how to find, create and analyze data to tell news stories with public service impact. Uses relational databases, advanced queries, basic statistics, and mapping to analyze data for storytelling. Assignments may include stories, blog posts, and data visualizations, with at least one in-depth project based on data analysis. Prerequisites: COMM 273D or Journalism M.A. student.
Terms: Win | Units: 4 | Repeatable for credit | Grading: Letter or Credit/No Credit
Instructors: Phillips, C. (PI)

COMM 277A: Computational Journalism (COMM 177A)

Focuses on using data and algorithms to lower the cost of discovering stories or telling stories in more engaging and personalized ways. Project based assignments based on real-world challenges faced in newsrooms. Prior experience in journalism or computational thinking helpful. Prerequisite: Comm 273D, COMM 113/213, or the consent of instructor.
Terms: Spr | Units: 4 | Grading: Letter or Credit/No Credit
Instructors: Nguyen, D. (PI)
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