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I am writing to pass along announcements for two visualization courses happening this fall in CCIS: Data Science 4200 “Information Presentation and Visualization" (undergraduate level), and Computer Science 7290 “Special Topics in Data Science: Visualization for Network Science" (graduate level). Both classes have some remaining seats for students interested in registering. In addition, the NUVis website has a growing list of all visualization courses offered at Northeastern across the university: http://nuvis.northeastern.edu/resources/ Best, Michelle —————————————————— CS 7290 Special Topics in Data Science: Visualization for Network Science Fall 2017 -- Prof. Cody Dunne (Scott)<https://www.ccis.northeastern.edu/people/cody-dunne/> -- [log in to unmask]<mailto:[log in to unmask]> Time and location: Tuesdays 11:45 am - 1:25 pm, Thursdays 2:50 pm - 4:30 pm in Ryder Hall 128 Website: https://codydunne.github.io/cs7290-f17/ Analyzing network data structures involves understanding the complex relationships between entities as well as any metadata or statistics associated with them. By encoding this data as an information visualization, we are able to leverage the impressive human visual bandwidth so that users can spot clusters, gaps, trends, outliers within a fraction of a second and communicate their results. This course will cover the principles of information visualization in the specific context of network science. It will introduce students to visually encoding data, interaction principles, human subjects evaluations, common techniques, and algorithms. The final grade will be composed of homework assignments, in-class quizzes, participation, and a service learning visualization project. —————————————————— DS 4200 Information Presentation and Visualization Fall 2017 — Prof. Michelle Borkin<http://www.ccis.northeastern.edu/people/michelle-borkin/> — [log in to unmask]<mailto:[log in to unmask]> Time and location: Tuesdays and Fridays from 9:50am - 11:30am in Ryder Hall 147 Website: http://www.ccs.neu.edu/home/borkin/courses/2017Fall/DS4200/ Introduces foundational principles, methods, and techniques of visualization to enable creation of effective information representations suitable for exploration and discovery. Covers the design and evaluation process of visualization creation, visual representations of data, relevant principles of human vision and perception, and basic interactivity principles. Studies data types and a wide range of visual data encodings and representations. Draws on examples from physics, biology, health science, social science, geography, business, and economics. Emphasizes good programming practices for both static and interactive visualizations. Creates visualizations in Excel and Tableau as well as Python and open web-based authoring libraries (e.g., D3). Requires programming in Python, JavaScript, HTML, and CSS. Requires extensive writing including documentation, explanations, and discussions of the findings from the data analyses and the visualizations. Preq: CS 2510, or by permission of the instructor. NUPath Attributes: With Service Learning, Analyzing/Using Data, NU Core Experiential Learning, Integration Experience, Writing Intensive. ######################################################################## To unsubscribe from the NUVIS-LIST list, click the following link: https://listserv.neu.edu/cgi-bin/wa?SUBED1=NUVIS-LIST