9:00am to 6:00pm
Mode of Training:
Facilitated Learning (F2F), Supervised Field Training and Project Work
Unlike the usual short courses where participants learn skills and concepts from the course, the proposed project-focused course seeks to offer project-solution training complemented with classroom training in data wrangling, analytics and modelling techniques. Participants will be guided to establish a suitably scoped data analytics project and will also be guided on undertaking solution steps, in the project. The training will provide a step by step exposure on applying the Microsoft Excel & KNIME related skills and concepts to realise successful analytics of the data studied.
1. Enables participants to apply knowledge in a step-by-step process, required for handling analytics projects.
2. Equips participants with necessary skills in Microsoft Excel for data wrangling, data cleaning, transformation and conditioning.
3. Facilitates participants to use an appropriate data analytics tool, like KNIME, for implementation of data modelling and machine learning techniques to perform analysis and inference based on modelling outcomes.
4. Enables participants to interpret results, establish process insights and make critical decisions.
By the end of the course, participants will be able to with their dataset:
• Appreciate the data available for study;
• Scope the data analytics project;
• Apply techniques relevant for data transformation & conditioning;
• Derive and Include relevant data fields required for analytics;
• Choose appropriate analytics or data modelling technique required for the project;
• Differentiate between data analysis and data analytics;
• Use appropriate functions / visuals readily available in the software used for the project;
• Identify the do’s and don’ts in a data analytics project;
• Build a model that represents the data and that meets the requirements of the project.
Topics to be covered
1. Project understanding and acquired relevant data
2. Relevant data wrangling training 1
3. Written Test for data wrangling following training 1
4. Relevant data analytics training 2
5. Assessment following training 2
6. Closely guided coaching for project execution
7. Independent application of learning into practice
8. Project: Analytics model demonstration and presentation
Data Analyst / Associate Data Engineer / Business Intelligence Manager / Data Engineer / AI / ML Engineer / Data Scientist / AI Scientist / Process Development/MS&T Engineer / Production Engineer / Biotechnologist / Assistant Project Manager /Project Management Executive / Assistant Civil and Structural Engineer / Technical Executive(Civil and Structural Engineering) / Production Supervisor / QC Technician/ QC Assistant/ Laboratory Technician / Assistant Market Development Manager/Market Development Executive
Minimum Entry Requirements / Assumed Skills and Knowledge
At least 2 years of work experience;
Have a fair experience using Microsoft Excel;
GCE O level with pass in English & Mathematics.
Award / 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 Performance (electronic Certificate will be issued)
A Certificate of Performance will be awarded to participants who pass the assessment and meet at least 75% attendance rate
Full Fees (before GST): $6,000.00
GST payable for all funding-eligible applicants*: $126.00
GST payable for others: $420.00
|Applicants/Eligibility||SkillsFuture Funding||Subsidised Fee (after GST)|
|Singapore Citizens aged 40 and above1||$5,400.00||$726.00 |
|Singapore Citizens aged below 40||$4,200.00 ||$1,926.00|
|Singapore Permanent Residents and LTVP+ Holders||$4,200.00 ||$1,926.00|
|SME-sponsored Singapore Citizens, Permanent Residents and LTVP+ Holders2||$5,400.00||$726.00 |
|Others (Full fees payable)||$0.00||$6,420.00|
*As per SSG’s policy, the GST payable is calculated based on 7% of the baseline funding subsidy of 70%
Singaporeans aged 25 years and above may use **SkillsFuture Credit balance to offset respective course fees.
1Under 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.
Please click here for more information on funding incentives.
Eligible for SkillsFuture CreditTerms and Conditions*Please note that once the maximum class size is reached, the online registration will be closed. You may register your interest, and would be notified if there is a new run.
1. All applications must be made via Online Registration at www.pace.sp.edu.sg
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:
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.