DAT 320 - Data Analytics II

Credit(s) 3.00
Lecture Hours: 3.00
Through this course, students will learn the fundamental concepts of data mining with extensive hands-on experience in applying the concepts to real-world applications. Students will have an in-depth knowledge of the following statistics principles: Introduction to data mining, Data and Preprocessing, Classification, Clustering, Association Analysis, Anomaly Detection, and Data Mining Case Studies.

Prerequisite(s): DAT 310
SLOs:
Upon successful completion of this course, students will be able to:

Develop and refine decision-making skills by basing decisions upon the outcome of statistical tests.
Analyze real-world scenarios and determine the appropriate type of analytical problem-solving techniques to utilize.
Interpret the results of print-outs (Classification, Clustering, Association Analysis, Anomaly Detection, etc) generated from appropriate data mining software.
Understand the reasoning/basis behind each statistical test.
Interpret the statistical results in a report format.