course-banner-img Data Analytics-1

Data Analytics for Electronics Industry

Topic:Data Analytics & Visualisation, Others

Course Type:Short & Modular Courses

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  • Course Date:

    11 Dec 2023 to 11 Dec 2023
  • Registration Period:

    22 Nov 2023 to 05 Dec 2023
  • Time:

    08:30 AM to 05:30 PM,
    8 hours / 1 day
  • Mode of Training:

    Facilitated Learning (Online Synchronous)
  • Venue:

  • Funding:

    Eligible for SkillsFuture Credit

This course introduces the fundamentals of data analytics and various tools such as data wrangling, data visualisation and data analytics which is one of the enablers of industry 4.0 to improve operational efficiency and business processes.

Course Objective

The objective of this course is to equip participants with knowledge of fundamentals of data analytics. Participants will also be able to apply these analysis tools to their data when designing and developing their future intelligent systems for the electronics &semiconductor industries. There would be hands-on session with the data analysis tools such as data wrangling, visualisations, regression models and prediction. Participants can apply the knowledge and skills to help improve their operational tasks and increase work productivity.

Course Outline

This course consists of 8 hours of lectures and practical.

MODULE 1:  Introduction to data analytics and data wrangling
Introduction to the needs for data analytics in electronics industry and big data analytics. 
Introduction to data wrangling and its application on data for the electronics industry.
Participants will be introduced to the needs of data analysis and various big data aspects and data wrangling, followed by a practical session on transforming and mapping raw data sets for further visualisation and analysis.

MODULE 2: Data Visualization and Unsupervised Data Analytic Techniques
Introduction to techniques for data visualization and unsupervised data analysis and their application on data.
Participants will be introduced to graphical visualisation methods and data analysis techniques of clustering and forecasting. They will also apply these techniques on data and will present the results in various graphical formats on an interactive dashboard to gain meaningful insights for process, equipment or quality control in manufacturing.

MODULE 3: Supervised Data Analytic Techniques 
Introduction to supervised data analytic techniques and their application on data.
Participants will apply data analysis techniques of linear regression, logistic regression and correlation on data and present the results in various graphical formats on an interactive dashboard to gain meaningful insights for manufacturing.
Discussion on applications of data analytics in electronics & semicon industry.

Minimum Requirements

Engineering or manufacturing background. Preferred to have at least an ITE level or above or at least a year of work experience in a technical role.

Certification / Accreditation

• Certificate of Attendance (electronic Certificate will be issued)
A Certificate of Attendance will be awarded to participants who meet at least 75% attendance rate

• Certificate of Completion (electronic Certificate will be issued)
A Certificate of Completion will be awarded to participants who pass the assessment and meet at least 75% attendance rate

Suitable for

All engineering technical or personnel.

Course Fees

The course fees payable above are inclusive of prevailing GST rate.

Applicants/Eligibility SkillsFuture Funding GST* Subsidised Fee (after GST)
Singapore Citizens aged 40 and above¹ $297.00 $7.92 $40.92
Singapore Citizens aged below 40 $231.00 $7.92 $106.92
Singapore Permanent Residents and LTVP+ Holders $231.00 $7.92 $106.92
SME-sponsored Singapore Citizens, Permanent Residents and LTVP+ Holders² $297.00 $7.92 $40.92
Others (Full fees payable) $0.00 $26.40 $356.40

*As announced at Budget 2022, there will be no increase in government fees and charges for Singaporeans from 1 Jan 2023 to 31 Dec 2023. Also, as per SSG’s policy, the GST payable for all funding-eligible applicants is calculated based on prevailing GST rate after baseline funding subsidy of 70%

Singaporeans aged 25 years and above may use **SkillsFuture Credit balance to offset respective course fees.

1 Under the SkillsFuture Mid-career Enhanced Subsidy. For more information, visit the SkillsFuture website here
2 Under the Enhanced Training Support for Small & Medium Enterprises (SMEs) Scheme. For more information of the scheme, click here. To view SP’s list of similar funded courses, click here. Please submit the attached “Declaration Form for Enhanced Training Support Scheme for SME” together with your online application.

Funding Incentives

Please click here for more information on funding incentives.

Application Procedure

1. All applications must be made via Online Registration at
Course fees can be paid by the following payment modes:

a) Credit Cards, Internet Banking, NETS (Not Applicable for company sponsored)
For e-payment using Visa/Master cards and Internet Banking, please click on the ‘Make e-Payment’ button on the acknowledgement page to proceed.

b) For NETS payment, you can pay at:
Singapore Polytechnic
One-Stop Service Centre

c) For payment via PayNow, please enter the UEN No. T08GB0056ACET and indicate the invoice/registration number. 

*With effect from 1 August 2021, cheque payment will not be available.

2. All successful applicants will be notified with a letter of confirmation via email.

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