IS 490 RB2 - Advanced Topics Info Studies - Advanced Data Science
Directed and supervised investigation of selected topics in information studies that may include among others the social, political, and historical contexts of information creation and dissemination; computers and culture; information policy; community information systems; production, retrieval and evaluation of knowledge; computer-mediated communication. Course Information: Additional fees may apply. See Class Schedule. 2 to 4 undergraduate hours. 2 to 4 graduate hours. May be repeated. Prerequisite: For undergraduates, junior standing and IS 202, or consent of instructor. Class Schedule Information: Class materials fee or field trip fee may be required.
NOTE: Students must be registered for this course by 4 pm on Wednesday January 17, 2018. No new students will be allowed to register for this class after that. This course will introduce advanced data science concepts by building on the foundational concepts presented in INFO 490: Foundations of Data Science. Students will first learn how to perform more statistical data exploration and constructing and evaluating statistical models. Next, students will learn machine learning techniques including supervised and unsupervised learning, dimensional reduction, and cluster finding. An emphasis will be placed on the practical application of these techniques to high-dimensional numerical data, time series data, image data, and text data. Finally, students will learn to use relational databases and cloud computing software components such as Hadoop, Spark, and NoSQL data stores. Students must have access to a fairly modern computer, ideally that supports hardware virtualization, on which th
Option 1Number of Required Visit(s): 0
Course Level: Graduate
Credit: 3 hr