University of Wyoming MA 5490-01/COSC 5010-02, 2019 Fall

Tuesday and Thursday, 9:35-10:50, 241 Ross Hall

Office Hours: T/R 1:00-2:00 and F 3:00-4:00

Professor Craig C. Douglas

Big Data and Mining

Course Descriptions

Graduate version: Data mining is a paradigm to find hidden data and anomalies in data sets, data bases, or data streams. The data can be either static or dynamic and can come from streams that are not saved. This course also provides an overview of MapReduce-like systems, hash table methods, finding data in files and data streams. Machine learning is a pardigm in which computers can learn without explicit programming. The learning can be unsupervised, supervised, or reinforced. The course provides an overview of clustering, perceptrons, support vector machines, neural networks, and dimension reduction methods.

Undergraduate version: The course is similar to the graduate level course. More background material is provided and fewer assumptions about a student's background knowledge is assumed.

Prerequisites

An eclectic group of students who are not afraid to program or use a computer and manipulate data in new ways.

Office

227 Ross Hall

Office Hours

Suggested Reading

Note for Computer Science Graduate Students

Computer Science graduate students may use the course to satisfy either the Artificial Intelligence or Systems: Networking, Distributed Computing, and Data Management breadth areas, but not both.

Cheers,
Craig C. Douglas

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