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DATA MINING FOR CORRELATION ANALYSIS (DM-LITE)* (16 HOURS)

Data Mining for Correlation Analysis
*This is a non-WSQ module.

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.

As 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



Webinar

Watch our webinar video for "Minimising Design of Experiments (DoE) for Process Optimisation Using Data Mining Approach" held on 7 May 2021 for more information about SIMTech's Data Mining Courses.

Watch Playback



Course Outline

Course Outline

The programme consists of 4 learning stages.
Stage 1
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.

Stage 2
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.

Stage 3
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.

Stage 4
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

Data Mining for Correlation Analysis_A4

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 course schedule.

Upon Completion of This Course

UPON COMPLETION OF THIS COURSE

Participants will be awarded with a Certificate of Attendance (COA) by SIMTech if they meet the following criteria:

  • Achieve at least 75% course attendance;
  • Take all assessments; and
  • Pass the course.

Pre-Requisites, Full and Nett Course Fees

Pre-Requisites

  • Applicants should possess a degree in any discipline or a diploma with a minimum of 3 years of related working experience.
  • Applicants who do not have the required academic qualifications are still welcome to apply, but shortlisted candidates may be required to attend an interview for special approval.
  • Proficiency in written and spoken English.

Full Course Fee

The full course fee for this module is $1,600 before funding and prevailing GST.

Nett Course Fee

International
Participants
Singapore Citizens
(39 yrs old or younger), SPRs or LTVP+ Holders
Singapore Citizens
(40 yrs or older)²
Enhanced Training Support
for SMEs¹
$1,712
$513.60 $193.60 $193.60
All fees are inclusive of prevailing GST.
LTVP+ Holders = Long Term Visit Pass Plus Holders

Please note that fees and funding amount are subject to change.

Singaporeans aged 25 years old and above are eligible for SkillsFuture Credit which can be used to offset course fees (for self-sponsored registrations only).

For more information on the SkillsFuture funding schemes you are eligible for, please visit www.ssg.gov.sg




How course fees are calculated




Contact Us




Brochure and Registration

Data Mining for Correlation Analysis_A4

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 course schedule.



Schedules

Module 
Skills Course Reference Number Training Period
(Click on dates to view schedules)
Registration Status
Implement Manufacturing Data Mining Techniques (42 hours) TGS-2020506158


Data Mining for Correlation Analysis (DM-LITE) TGS-2020504604    

Sessions
FD : Full Day  AM : Morning PM : Afternoon EVE : Evening 




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