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CASL - Data Analytics and Visualization with R

Sessions 2 days
Duration 16 hrs
Level Intermediate
Assessment 2 hrs

Venue

12 Woodlands Square #07-85/86/87 Woods Square Tower 1, Singapore 737715. 5 mins walk from Woodlands (NS9) MRT station.

The venue is disabled-friendly.

TSC Title: Analysis of Research Data
TSC Code: HCE-DAT-4008-1.1

Funding for this course is valid from 21 Jul 2026 to 20 Jul 2027. Register and complete the course within this period to qualify for funding support.

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.

Download Course Brochure

Certificate of Achievement from Tertiary Infotech Academy Pte Ltd - Upon meeting at least 75% attendance and passing the assessment(s), participants will receive a Certificate of Achievement from Tertiary Infotech Academy Pte Ltd.

CASL - Data Analytics and Visualization with R

Course Code: TGS-2026064475

CASL
SFC
PSEA
UTAP
SFEC
Absentee Payroll
MCES

44 Review(s) | Add Your Review

Master the art of transforming raw data into actionable insights with our CASL-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.

Full Fee $750.00 Before GST

GST $67.50 9% of fee

Baseline Nett $442.50 SG/PR age 21+ · 50% funded

MCES / SME Nett $292.50 SG age 40+ · 70% funded

SkillsFuture Enterprise Credit (SFEC)

Eligible Singapore-registered companies can tap on $10000 SFEC to cover out-of-pocket expenses.

View on SkillsFuture for Business

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.

Direct Application on SkillsFuture Portal

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.

Submit UTAP Claim

PSEA

Eligible Singapore Citizens can use their PSEA funds to offset course fee payable after funding.

Check PSEA Eligibility

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, then submit the completed form to us:

PSEA Withdrawal Form Submit PSEA Form

Please bring your own laptop for hands-on training. If you don't have laptop, we can provide spare laptop for training use.

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.

You can register your interest without upfront payment. There is no penalty for withdrawal of the course before the class commences.
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

Written Exam
Practical Exam

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 SWDA's (formerly 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 SWDA's (formerly 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), SWDA 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

SWDA 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 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 is Head of Data Science at Plano Pte. Ltd. and an ACLP-certified trainer with deep expertise in data analytics, machine learning, and AI applications. He has extensive hands-on experience developing predictive models, RShiny dashboards, and deep learning solutions using R, Python, TensorFlow, and Keras. With a strong professional background in healthcare, finance, and customer analytics, Dwight brings an applied perspective to teaching AI, focusing on both the opportunities and risks of emerging technologies.

Khoo Yong is an ACTA-certified trainer with a strong foundation in adult education and applied analytics. With years of experience in training and mentoring learners, he specializes in simplifying complex concepts in data analysis and statistical methods for beginners. His expertise includes guiding participants in applying R programming to perform descriptive statistics, hypothesis testing, and data visualization, equipping them with practical skills to analyze data effectively and interpret results with confidence. As a certified adult educator, Khoo Yong ensures his training is engaging, structured, and accessible to learners from diverse backgrounds. He emphasizes hands-on practice with R, enabling participants to bridge theory with application in real-world contexts. His learner-centered approach not only builds technical competency but also fosters analytical thinking, preparing participants to use statistical tools in business, research, and decision-making.

Review

Customer Reviews (44)

Insightful and knowledgeable trainer 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

I had the opportunity to attend Dr Alvin Ang's R Tidyverse Data Analytics and Visualization training, and I found him to be a very insightful and knowledgeable trainer. What I appreciated most was how he connected the technical concepts with practical, real-world applications. He went beyond simply teaching R and the Tidyverse tools, and shared valuable insights into how data analytics is actually applied in the industry. As someone who is relatively new to the data analytics field, I found his industry perspectives especially valuable. He gives practical perspectives on the skills, expectations, and continuous learning needed to progress in this field. He also took the time to share additional learning resources and introduce me to a social network of data scientists, giving me opportunities to continue learning even after the training has ended. Overall, I found Dr Alvin to be an engaging, practical, and supportive trainer with strong industry knowledge. (Posted on 8/22/2026)

Well-structured, engaging and easy to follow 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

I had the pleasure of learning R Data Analytics and Visualization under Dr Alvin Ang at Tertiary Infotech. His lessons were well-structured, engaging, and easy to follow, allowing even complex R programming concepts to be understood with confidence. Through a combination of clear explanations, practical examples, and hands-on exercises, he created an enjoyable and highly effective learning experience. Throughout the course, Dr Alvin covered a comprehensive range of topics including data wrangling with the tidyverse, data visualization using ggplot2, data manipulation with dplyr, tidyr and readr, piping with %>%, text mining using wordcloud, and statistical analysis techniques that are highly relevant to real-world data analytics. He was always patient, approachable, and willing to answer questions, ensuring that every participant understood the concepts before moving forward. Beyond the classroom, Dr Alvin generously shared additional learning resources, industry insights, and practical career advice to support our continued learning journey. I would highly recommend Dr Alvin Ang to anyone looking to build a strong foundation in R programming, data analytics, and data visualization. His passion for teaching and depth of knowledge make him an outstanding trainer and mentor. (Posted on 8/6/2026)

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