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SE 512. Data Mining for Software Engineering

Department: Computer Science
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: SE 640
Semester Offered: DEMAND
Grading Method: ABCDF
Permissions: Permission of instructor

Student Learning Outcomes

1. Identify data mining concepts and technologies
2. Identify the different types of data, their statistical description, and similarity/dissimilarity measures
3. Apply basic data pre-processing techniques
4. Derive interesting patterns using frequent pattern mining techniques
5. Apply and predict future instances using supervised learning techniques (classification)
6. Apply cluster analysis techniques to group similar data (unsupervised learning)
7. Use a variety of data mining tools

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