Data Mining for Software Engineering
General
Prefix
SE
Course Number
412
Course Level
Undergraduate
Department/Unit(s)
College/School
College of Science and Engineering
Description
Mining interesting information from large data sets. Statistical analysis and machine learning, data mining concepts and techniques, data representation and their similarity/dissimilarity measures, data pre-processing, frequent pattern mining, supervised and unsupervised modeling.
Prerequisites
Credits
Min
3
Max
3
Repeatable
No
Goals and Diversity
MN Goal Course
No
Cultural Diversity
No
Learning Outcomes
Outcome
Identify data mining concepts and technologies.
Outcome
Identify the different types of data, their statistical description, and similarity/dissimilarity measures.
Outcome
Apply basic data pre-processing techniques.
Outcome
Derive interesting patterns using frequent pattern mining techniques.
Outcome
Apply and predict future instances using supervised learning techniques (classification).
Outcome
Apply cluster analysis techniques to group similar data (unsupervised learning).
Outcome
Use a variety of data mining tools.
Course Outline
Course Outline
Dependencies
Programs
SE412
is a
completion requirement
for: