Course Description
This course emphasizes on the principal concepts of Data Mining and Data Warehousing techniques. Data Mining concepts include: Data Mining cycles, Data Mining methodology, major issues in Data Mining, data preprocessing stages (data cleaning, data integration, data reduction, data transformation and data discretization), data visualization, and measurement of the effectiveness of data mining. The course goes further into data warehousing and analytical processing techniques including: data warehouse modeling (data cubes and OLAP), mining frequent patterns, associations, correlations, classifications (such as decision trees, neural networks, Bayes classification, rule-based classification) and cluster analysis methods (such as partitioning, hierarchical, density-based, and grid-based approaches). As part of this course, students will be trained on latest data mining software.
Course ID: CIS 457
| Credit hours | Theory | Practical | Laboratory | Lecture | Studio | Contact hours | Pre-requisite |
|---|---|---|---|---|---|---|---|
| 3 | 4 | 4 | - |
