The programme consists of 4 learning stages.
|Trainees will learn up-to-date data mining technologies through an overview of data mining introduction. They will also gain knowledge of the successful applications of data mining in local industry companies through case-studies sharing.|
|Trainees will learn to carry out data collection and data pre-processing. They will also learn how to use K-means clustering to discover anomaly data patterns. They will have an opportunity to use data mining software to carry out hands-on sessions to understand the k-means clustering method.
|Trainees will learn about correlation analysis for major factor identification. They will also learn the fundamental of predictive modelling by multiple regression. A smart design of experiment (DoE) with what-if analysis will be carried out based on a predictive model. For each of the learning point, trainees will be given an opportunity to try and apply what they learned through hands-on sessions.|
|Trainees will learn about Artificial Intelligence (AI) methods. The basics of Neural Networks (NN) and Fuzzy Neural Networks (FNN) will be introduced. The trainees will learn how to apply NN and FNN for performance prediction through hands-on sessions. They will also have an opportunity to compare the advantage and disadvantage of predictive modelling methods through a case study. The trainees will gain a solid foundation and apply what they have learned.|
Brochure and Registration
Please register for this course under 1. Modular Programmes > 2. Implement Manufacturing Data Mining Techniques > 3. Data Mining for Correlation Analysis (DM-LITE) in the online registration form.
Note: Received registrations are placed on the waiting list for the next
upcoming intake if the current intake is full or there is no available