Introduction
Data mining is a technique used to extract useful information from a large number of datasets. A good understanding of the updated data mining techniques and the ability to use effectively is increasingly important for data-intensive manufacturing operations.
This training is targeted towards manufacturing companies and companies in other industries which are data rich but information poor. It aims to provide the trainees understanding of
up-to-date data mining technologies, build a fundamental about data analytics and data mining techniques for various applications such as process optimisation, correlation analysis for major factor identification, product quality improvement and many more.
about the programme
This course aims to provide participants with up-to-date technologies in data mining. Through extensive hands-on and sharing of successful case studies, it allows the participants to have the confidence and ability to use data mining techniques to help them in their daily work.
The course will provide the participants with a set of methodology for conducting
problem-solving using data mining. From the basics of methodologies in data collection,
pre-process data from multiple sources, cleaning of the data, to finally using data mining techniques to analyse the data and solve actual industrial problems.
At the end of the course, the participants can:
- Understand the fundamentals of data mining technologies
- Gain knowledge of actual industry case studies of how data mining can be used to solve actual industrial problems
- Understand data collection and pre-process methodologies
- Understand the K-means clustering method and its application
- Able to apply correlation analysis to identify the major factors for root cause analysis
- Understand and apply predictive modelling by multiple regression and neural networks
- Apply smart design of experiment with What-If analysis through predictive models
Who Should Attend
This course is designed for professionals such as engineers, managers, researchers, IT support staff as well as management in semiconductor, electronics, precision engineering, aerospace, automation, medtech, pharmaceutical and logistic industries.