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| 02/04 - 05/20 | ||||||
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5:45 pm |
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Subject: Software Eng (Grad) (SEIS)
CRN: 21453
Lecture
St Paul: O'Shaughnessy Science Hall 333
Requirements Met:
LLM/MSL Elective
Software Technical Elective
The course provides an introduction to concepts and techniques used in field of data analytics and visualization. Data analytics is defined to be the science of examining raw data with the purpose of discovering knowledge by analyzing current and historical facts. Insights discovered from the data are then communicated using data visualization. Topics covered in the course include predictive analytics, pattern discovery, and best practices for creating effective data visualizations. Through practical application of the above topics, students will also develop proficiency in using analytics tools.
3 Credits