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WSQ - Data Analytics and Visualization with R

WSQ - Data Analytics and Visualization with R

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Master the art of transforming raw data into actionable insights with our WSQ-endorsed course in Data Analytics and Visualization with R. This comprehensive course covers everything from basic data manipulation in R to advanced visualization techniques. You'll learn how to prepare datasets, create compelling visuals, and make data-driven decisions. The curriculum also includes real-world projects to ensure you get the hands-on experience you need.

Upon course completion, you will be fully equipped to tackle any data analysis or visualization challenge that comes your way. Whether you're looking to expand your career options, improve business decision-making, or delve deeper into data science, this course provides the fundamental skills to set you on the path to success. Boost your data analytics game today with our specialized training.

Learning Outcomes

By end of the course, learners should be able to

LO1: Prepare and transform data for analysis.
LO2: Summarise data with descriptive statistics.
LO3: Perform quantitative data analysis.
LO4: Perform quantitative data analysis.
LO5: Perform data visualizations to interpret data.

Course Brochure

Download WSQ - Data Analytics and Visualization with R Brochure

Skills Framework

This course follows the guideline of Analysis of Research Data HCE-DAT-4008-1.1 TSC under Healthcare Skills Framework

Certification

Certificate of Completion from Tertiary Infotech - Upon meeting at least 75% attendance and passing the assessment(s), participants will receive a Certificate of Completion from Tertiary Infotech.
OpenCerts from SkillsFuture Singapore - After passing the assessment(s) and achieving at least 75% attendance, participants will receive a OpenCert (aka Statement of Achievement) from SkillsFuture Singapore, certifying that they have achieved the Competency Standard(s) in the above Skills Framework.

WSQ Funding

WSQ funding is only applicable to Singaporeans and PR. Subject to eligibility, the funding support is subjected to funding caps.

Effective for courses starting from 1 Jan 2024
Full Fee	GST	Nett Fee after Funding (Incl. GST)
		Baseline	MCES / SME
$750.00	$67.50	$442.50	$292.50

Baseline: Singaporean/PR age 21 and above
MCES(Mid-Career Enhanced Subsidy): S'porean age 40 & above

Upon registration, we will advise further on how to tap on the WSQ Training Subsidy.

You can pay the nett fee (after the WSQ training subsidy) by the following :

SkillsFuture Enterprise Credit (SFEC)

Eligible Singapore-registered companies can tap on $10000 SFEC to cover out-of-pocket expenses.Click here to submit SkillsFuture Enterprise Credit

SkillsFuture Credit (SFC)

Eligible Singapore Citizens can use their SFC to offset course fee payable after funding but the $4,000 Additional SFC (Mid-Career Support) cannot be used. Click here for SkillsFuture Credit submission

UTAP

Eligible NTUC members can apply for 50% of the unfunded fee from UTAP, capped up to $250/year and for members aged 40 and above, capped up to $500/year. Click here to submit UTAP

PSEA

Eligible Singapore Citizens can use their PSEA funds to offset course fee payable after funding. Please inform us if you intend to use your PSEA funding.

To check for Post-Secondary Education Account (PSEA) eligibility for this course, Visit SkillsFuture (course code: TGS-2020504413)

Scroll down to “Keyword Tags” to verify for PSEA eligibility.
If there is “PSEA” under keyword tags, the course is eligible for PSEA.

Once you are eligible for PSEA, please download and fill up the PSEA Withdrawal Form and email to us.

Course Code: TGS-2020504413

Post-Course Support

We provide free consultation related to the subject matter after the course.
Please email your queries to enquiry@tertiaryinfotech.com and we will forward your queries to the subject matter experts.

Course Cancellation/Reschedule Policy

You can register your interest without upfront payment. There is no penalty for withdrawal of the course before the class commerce.
We reserve the right to cancel or re-schedule the course due to unforeseen circumstances. If the course is cancelled, we will refund 100% for any paid amount.
Note the venue of the training is subject to changes due to availability of the classroom

Course Details

Topic 1: Data Preparation and Transformation

Overview of Data Analysis of Research Data
Install R Data Analysis Packages - Tidyverse and ggplot2
Import and Export Dataset
Filter and Slice Data
Clean Data
Join Data
Transform Data
Aggregate Data
Pipe Data

Topic 2: Data Summary

Categorical vs Continuous Data
Quantitative vs Qualitative Data
Descriptive Statistics of Data
Summarize Data
Basic Plots and Tables

Topic 3: Quantitative Data Analysis

Quantitative Data Analysis Overview
Correlation Analysis
Regression Analysis
Hypothesis Testing
Analysis of Variances (ANOVA)

Topic 4: Qualitative Data Analysis

Qualitative Data Analysis Overview
Install R Packages for Qualitative Data Analysis
Word Cloud Analysis
Text Analysis

Topic 5: Data Visualization

Grammar of Graphics
Plots for Quantitative Data
Plots for Qualitative Data
Customize Visualizations
Interpret Findings

Final Assessment

Written Assessment - Short Answer Questions (WA-SAQ)
Practical Performance (PP)

Course Info

Promotion Code

Promo or discount cannot be applied to WSQ courses

Minimum Entry Requirement

Knowledge and Skills

Able to operate using computer functions with minimum Computer Literacy Level 2 based on ICAS Computer Skills Assessment Framework
Minimum 3 GCE ‘O’ Levels Passes including English or WPL Level 5 (Average of Reading, Listening, Speaking & Writing Scores)

Attitude

Positive Learning Attitude
Enthusiastic Learner

Experience

Minimum of 1 year of working experience.
Minimum 18 years old

Minimum Software/Hardware Requirement

Software:

You can download and install the following software:

Hardware: Windows and Mac Laptops

About Progressive Wage Model (PWM)

The Progressive Wage Model (PWM) helps to increase wages of workers through upgrading skills and improving productivity.

Employers must ensure that their Singapore citizen and PR workers meet the PWM training requirements of attaining at least 1 Workforce Skills Qualification (WSQ) Statement of Attainment, out of the list of approved WSQ training modules.

For more information on PWM, please visit MOM site.

Funding Eligility Criteria

Individual Sponsored Trainee

Employer Sponsored Trainee

Singapore Citizens or Singapore Permanent Residents of age 21 and above
From 1 October 2023, attendance-taking for SkillsFuture Singapore's (SSG) funded courses must be done digitally via the Singpass App. This applies to both physical and synchronous e-learning courses.
Trainee must pass all prescribed tests / assessments and attain 100% competency.
We reserves the right to claw back the funded amount from trainee if he/she did not meet the eligibility criteria.

Singapore Citizens or Singapore Permanent Residents who are DIRECT EMPLOYEE of the sponsoring company.
From 1 October 2023, attendance-taking for SkillsFuture Singapore's (SSG) funded courses must be done digitally via the Singpass App. This applies to both physical and synchronous e-learning courses.
Trainee must pass all prescribed tests / assessments and attain 100% competency.
We reserves the right to claw back the funded amount from the employer if trainee did not meet the eligibility criteria.

SkillsFuture Credit:

Eligible Singapore Citizens can use their SkillsFuture Credit to offset course fee payable after funding.

PSEA:

To check for Post-Secondary Education Account (PSEA) eligibility, goto mySkillsFuture portal and search for this course code.
Scroll down to "Keyword Tags" to verify for PSEA eligibility.
If there is “PSEA” under keyword tags, the course is eligible for PSEA.
And if there is no “PSEA” under keyword tags, the course is ineligible for PSEA.
Not all courses are eligible for PSEA funding.

Absentee Payroll (AP) Funding:

$4.50 per hour, capped at $100,000 per enterprise per calendar year.
AP funding will be computed based on the actual number of training hours attended by the trainee.

SFEC:

If the Training Provider has submitted an enrolment for course fee grant claim in Training Partners Gateway (TPGateway), SSG would be able to derive SFEC funding based on this record. There is no need for enterprise to submit any claim request and the SFEC claim will be automatically generated and disbursed.
Where there is no such record, eligible employers are required to submit an SFEC claim after course completion via the SFEC microsite.
SkillsFuture Enterprise Credit (SFEC) Microsite

Steps to Apply Skills Future Claim

The staff will send you an invoice with the fee breakdown.
Login to the MySkillsFuture portal, select the course you’re enrolling on and enter the course date and schedule.
Enter the course fee payable by you (including GST) and enter the amount of credit to claim.
Upload your invoice and click ‘Submit’

SkillsFuture Level-Up Program

The SkillsFuture Level-Up Programme provides greater structural support for mid-career Singaporeans aged 40 years and above to pursue a substantive skills reboot and stay relevant in a changing economy. For more information, visit SkillsFuture Level-Up Programme

Get Additional Course Fee Support Up to $500 under UTAP

The Union Training Assistance Programme (UTAP) is a training benefit provided to NTUC Union Members with an objective of encouraging them to upgrade with skills training. It is provided to minimize the training cost. If you are a NTUC Union Member then you can get 50% funding (capped at $500 per year) under Union Training Assistance Programme (UTAP).

For more information visit NTUC U Portal – Union Training Assistance Program (UTAP)

Steps to Apply UTAP

Note

SSG subsidy is available for Singapore Citizens, Permanent Residents, and Corporates.
All Singaporeans aged 25 and above can use their SkillsFuture Credit to pay. For more details, visit www.skillsfuture.gov.sg/credit
An unfunded course fee can be claimed via SkillsFuture Credit or paid in cash.
UTAP funding for NTUC Union Members is capped at $250 for 39 years and below and at $500 for 40 years and above.
UTAP support amount will be paid to training provider first and claimed after end of class by learner.

Appeal Process

The candidate has the right to disagree with the assessment decision made by the assessor.
When giving feedback to the candidate, the assessor must check with the candidate if he agrees with the assessment outcome.
If the candidate agrees with the assessment outcome, the assessor & the candidate must sign the Assessment Summary Record.
If the candidate disagrees with the assessment outcome, he/she should not sign in the Assessment Summary Record.
If the candidate intends to appeal the decision, he/she should first discuss the matter with the assessor/assessment manager.
If the candidate is still not satisfied with the decision, the candidate must notify the assessor of the decision to appeal. The assessor will reflect the candidate’s intention in the Feedback Section of the Assessment Summary Record.
The assessor will notify the assessor manager about the candidate’s intention to lodge an appeal.
The candidate must lodge the appeal within 7 days, giving reasons for appeal
The assessor can help the candidate with writing and lodging the appeal.
he assessment manager will collect information from the candidate & assessor and give a final decision.
A record of the appeal and any subsequent actions and findings will be made.
An Assessment Appeal Panel will be formed to review and give a decision.
The outcome of the appeal will be made known to the candidate within 2 weeks from the date the appeal was lodged.
The decision of the Assessment Appeal Panel is final and no further appeal will be entertained.
Please click the link below to fill up the Candidates Appeal Form.

Job Roles

Researchers
Data Analysts
Business Intelligence Analysts

Trainers

Dr Alvin Ang – Dr Alvin Ang is an ACLP-certified trainer with a Ph.D. in Operations Research from Nanyang Technological University. With more than a decade of academic and industry experience, he has taught data science, statistics, and machine learning at NTU, SUSS, Curtin University, and as an IBM Data Science Instructor. He is also the founder of DataFrens.sg, an open-source community promoting data science knowledge in Singapore. His professional background includes roles as a research fellow at NUS and consultant in data-driven business solutions, supported by multiple IBM certifications in R, Python, and data visualization.

In his R-based data analytics and visualization training, Dr Ang emphasizes practical, hands-on learning. He guides learners through data cleaning, statistical analysis, and visualization using R libraries such as ggplot2 and Shiny, ensuring participants can transform raw data into actionable insights. By blending theory with real-world case studies, he equips learners with both the technical skills and the confidence to communicate analytical findings effectively.

Dwight Nuwan Fonseka – Dwight Nuwan Fonseka is an ACLP-certified trainer and Head of Data Science at Plano Pte. Ltd., where he leads projects in predictive analytics, R-based modeling, and big data systems. He also serves as an adjunct lecturer at the London School of Business and Finance (LSBF), coordinating the Diploma in Data Analytics, and as an associate trainer with Tertiary Courses. His expertise spans R programming, R Shiny app development, and machine learning frameworks such as h2oAI and Keras, applied to healthcare, financial, and text mining projects.

In his training, Dwight focuses on beginner-to-advanced applications of R for analytics and visualization. His sessions cover descriptive and inferential statistics, time series forecasting, and advanced visualization using ggplot2 and Shiny dashboards. With his project-driven approach, Dwight ensures learners not only understand R concepts but also apply them effectively to real-world datasets for decision-making and reporting.

Khoo Yong – Khoo Yong is an ACTA-certified trainer with extensive experience in statistics, data analytics, and professional training. With a strong background in adult education, he specializes in breaking down complex concepts into simple, practical lessons suited for beginners. His teaching experience spans a wide range of WSQ programs, where he has equipped learners with the skills to apply data analysis in business and technical contexts.

In his training on R for data analytics and visualization, Khoo introduces participants to core concepts such as data preparation, descriptive statistics, and exploratory analysis. He emphasizes hands-on practice with R libraries to create visualizations and interpret patterns in datasets. By combining technical know-how with a learner-centered approach, Khoo ensures participants gain the confidence to apply R tools effectively in their workplace and professional projects.

Customer Reviews (42)

Average Rating: 2.7/5 Review by Course Participant/Trainee

1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment

N/A (Posted on 3/13/2026)

Average Rating: 2.0/5 Review by Course Participant/Trainee

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N/A (Posted on 3/13/2026)

Average Rating: 4.3/5 Review by Course Participant/Trainee

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2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment

N/A (Posted on 3/13/2026)

Average Rating: 4.0/5 Review by Course Participant/Trainee

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2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment

N/A (Posted on 3/13/2026)

Average Rating: 3.0/5 Review by Course Participant/Trainee

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2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment

Nil (Posted on 3/13/2026)

Average Rating: 5.0/5 Review by Course Participant/Trainee

1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment

N/A (Posted on 3/13/2026)

Average Rating: 3.0/5 Review by Course Participant/Trainee

1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment

N/A (Posted on 3/13/2026)

Recommended Review by Course Participant/Trainee

1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment

Great educator Dr Alvin Ang (Posted on 11/26/2025)

Recommended Review by Course Participant/Trainee

1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment

The course is very helpful for my work, thanks Dr. Alvin! (Posted on 11/26/2025)

Recommended Review by Course Participant/Trainee

1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment

. (Posted on 11/26/2025)

Recommended Review by Course Participant/Trainee

1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment

. (Posted on 11/26/2025)