Data Mining for Correlation Analysis (DM-LITE)
About This Course
Upon the completion of the course, learners will be able to:
1. Understand what is Data mining
2. Understand the common functions in data mining
3. Understand how data mining is applied by some of the local industry companies
4. Conduct effective data collection
5. Understand the importance of data pre-processing
6. Carry out data pre-processing methodologies
7. Know how to use k-means clustering for data noise filtering
8. Understand the theory of correlation analysis
9. Apply correlation analysis
10. Understand predictive modelling by regression
11. Apply predictive modelling by regression
12. Understand prediction modelling by neural network
13. Apply prediction modelling by neural network
14. Understand smart design of experiment through data mining methods
15. Apply smart design of experiment and what-If analysis through data mining methods
What You'll Learn
1. Up to date data mining technologies
2. Data collection and pre-processing methodologies
3. Correlation analysis knowledge and application
4. Regression analysis knowledge and application
5. Neural Network knowledge and application
6. Smart Design of Experiment methodologies
7. What-If analysis methodologies and application
Entry Requirements
Poly Diploma or equivalent and above.