Description:
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Course Description: In this course, students will be able to explore data mining hands-on by using data mining tools for pattern recognition, visualization, artificial intelligence and more.
Prerequisites: None
Learning Outcome:
– Examine foundational concepts in data mining
– Differentiate between descriptive and predictive elements of data mining
– Contrast the strengths and weaknesses of supervised and unsupervised methods
| Module |
Topic & Readings |
| Module 1 |
Foundations of Data Mining
Data Concepts
Data Quality |
| Module 2 |
Components of Data Mining
Pattern Recognition
Visualization and Large-Scale Data |
| Module 3 |
Methods for Data Mining
Supervised Machine Learning
Deep Learning |
Faculty: John Springer