ICS 412 Computational Data Mining
Data Mining involves an intelligent analysis and discovery of patterns information stored in data sets. It has gained a high attention among practitioners in a variety of industries and fields. Nowadays, almost every institution collects data, which can be analyzed in order to support making better decisions, improving policies, discovering computer network intrusion patterns, designing new drugs, detecting credit fraud, making accurate medical diagnoses, predicting imminent occurrences of important events, monitoring and evaluation of reliability to preempt failures of complex systems, etc. In this course, the students will be exposed to data mining concepts, techniques, and software utilized in the overall process of discovering knowledge within data.
First day attendance is mandatory.
Note: Students are responsible to both be aware of and abide by prerequisites for ICS courses for which they enroll, and will be administratively dropped from a course if they have not met prerequisites.
Prerequisites
Special information
Note: Students are responsible to both be aware of and abide by prerequisites for ICS courses for which they enroll, and will be administratively dropped from a course if they have not met prerequisites.
4 Undergraduate credits
Effective January 8, 2018 to present
Learning outcomes
General
- Explain the basic principles of the primary data mining technique.
- Classify data mining and data warehouse functionalities.
- Apply data preprocessing techniques-data cleaning, data integration and transformation, data reduction and concept hierarchy generation.
- Examine the current needs in data mining research.
- Design Models and use data mining software to perform data mining functionalities ¿ mining association rules, classification and prediction and decision tree analysis.