INFO 490 RB2 - Special Topics - Advanced Data Science

Description:

Topics of current interest. Course Information: 1 to 4 undergraduate hours. 1 to 4 graduate hours. May be repeated if topics vary. Prerequisite: Consent of instructor. Other prerequisites as specified for each topic offering. See Class Schedule.

Special Instructions:

Advanced Data Science: This class is an asynchronous, online course. 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 mod

Option 1

Number of Required Visit(s): 0

Course Level: Graduate

Credit: 3 hr

Term(s): Spring