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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 companies can use their $10,000 SFEC to cover up to 90% of out-of-pocket course fees for classes ending on or before 30 Nov 2026. A redesigned SFEC starts on 1 Dec 2026.

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

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 will need the following for this course:

R – free
RStudio Desktop – free

Hardware: Windows PC or Mac laptop

Funding Eligibility Criteria

Self-sponsored learners (individuals)

Singapore Citizens and Singapore Permanent Residents aged 21 and above.
Up to 50% course fee funding. Singapore Citizens aged 40 and above receive up to 70% under the Mid-career Enhanced Subsidy (MCES).
Singapore Citizens aged 25 and above can pay the remaining fee with SkillsFuture Credit.

Company-sponsored learners

Singapore Citizens and Singapore Permanent Residents who are direct employees of the sponsoring company.
Up to 50% course fee funding, or up to 70% for employees of SMEs (Enhanced Training Support for SMEs) and for Singapore Citizens aged 40 and above. An SME has no more than 200 employees or an annual turnover of no more than $100 million.
Employers can also claim Absentee Payroll funding for employees who attend during working hours.
Eligible companies can offset their out-of-pocket fees with SkillsFuture Enterprise Credit (SFEC).

Conditions for all funded learners

Attendance is taken digitally with Singpass for every session, including the assessment.
You must complete the course and pass all assessments (assessed as Competent).
If these conditions are not met, the funding is clawed back and the learner or employer pays the full course fee.
9% GST is charged on the full course fee before funding.
Promo and discount codes cannot be used on funded courses.
Any balance after funding can be paid in cash, with SkillsFuture Credit, with PSEA (Singapore Citizens with a PSEA), or partly reimbursed by UTAP for NTUC members.

How to Apply SkillsFuture Credit Claim for Individuals

Singapore Citizens aged 25 and above can use their SkillsFuture Credit (base tier) to pay the course fee after funding. The $4,000 mid-career top-up cannot be used for this course.

Register for this course as self-sponsored and tell us you will use SkillsFuture Credit. Do not pay the amount you plan to claim.
We email you an invoice showing the course fee after funding.
From 60 days before the course starts, and no later than the course start date, log in to MySkillsFuture with Singpass and click Claim credits.
Click Submit a Claim and search for this course by its course code, TGS-2026064475.
Select your class start date, enter the course fee payable after funding and the amount of credit to claim, then upload the invoice (PDF, JPG or PNG, under 4MB).
Review, accept the terms and click Agree and Submit. The credit is paid directly to us; processing can take up to 14 working days.

Changing or withdrawing: cancel the claim on MySkillsFuture at least one day before the course starts. If your class date changes, cancel the claim and submit a new one with the new date.

How to Apply SkillsFuture Enterprise Credit (SFEC)

SFEC helps companies pay for employee training. The current SFEC ends on 30 November 2026, and a redesigned SFEC starts on 1 December 2026.

Current SFEC: classes ending on or before 30 November 2026

Eligible companies received a one-off $10,000 credit, notified by letter to their Corppass administrator. Eligibility generally required at least 3 Singapore Citizen or PR employees and Skills Development Levy contributions.
SFEC covers up to 90% of the company's out-of-pocket course fee after other subsidies.

Check your company's SFEC eligibility and balance on EnterpriseSG.
Register your Singapore Citizen or PR employee for a class that ends by 30 November 2026, as company-sponsored, and pay the course fee after funding.
Your employee attends and completes the course. We submit the attendance and assessment results to SWDA.
No separate claim is needed. SFEC is calculated automatically once the course fee grant is approved and is paid quarterly to your company's IRAS GIRO or PayNow Corporate account.

Any unused balance of the current SFEC expires on 30 November 2026.

Redesigned SFEC from 1 December 2026

Companies with at least 3 resident employees receive a fresh $10,000 in an online SFEC wallet that offsets out-of-pocket fees upfront at enrolment, instead of reimbursing them afterwards. SWDA has not yet published the support rates and claim steps; see OurWorkforce or our SFEC guide.

How to Apply UTAP (NTUC Members)

NTUC members can claim 50% of the unfunded course fee under the Union Training Assistance Programme (UTAP), capped at $250 a year (aged below 40) or $500 a year (aged 40 and above). The cap is shared with UTAP claims for AI tool subscriptions.

Eligibility: you must be an NTUC member paying full membership fees, with your membership paid up before and during the course and when you claim. The course must not be fully paid for by your employer or another source.

Make sure your NTUC membership is paid up before the course starts.
Register for this course with us and pay the course fee after funding and SkillsFuture Credit.
Attend at least 75% of the course and sit all assessments.
Within 6 months after the course ends, go to the NTUC U Portal, open UTAP under E-services, log in with Singpass and choose Course Fee Claim.
Enter the nett course fee you paid (after all subsidies and SkillsFuture Credit, including GST), and upload your invoice or receipt and your certificate or result slip (PDF, JPG or PNG, up to 5MB each).
NTUC usually pays the claim within 4 weeks of submission.

How to Apply PSEA

Singapore Citizens with a Post-Secondary Education Account (PSEA), which stays open until around the year you turn 31, can use it to pay the course fee after funding for PSEA-approved courses. You can also use a sibling's PSEA after your own has been used up.

Check that this course shows the PSEA tag on its MySkillsFuture page.
Check your PSEA balance on MOE's Student Finance System with Singpass.
Download and complete the PSEA withdrawal form, then submit it to us.
We submit the withdrawal request to MOE. You (and your sibling, if you are using their account) authorise it in the Student Finance System. Nothing is withdrawn without this authorisation.
MOE pays us directly. If you have already paid, we refund the amount covered by PSEA.

More details: MOE PSEA overview.

Appeal Process

If you disagree with an assessment decision, you have the right to appeal.

When the assessor gives you feedback, say whether you agree with the outcome. If you agree, you and the assessor sign the Assessment Summary Record; if you disagree, do not sign it.
Discuss the decision with the assessor or the assessment manager first.
If you are still not satisfied, tell the assessor you intend to appeal. The assessor records this in the feedback section of the Assessment Summary Record and informs the assessment manager.
Lodge your appeal within 7 days, giving your reasons, using the Candidate Appeal Form. The assessor can help you write and lodge it.
An Assessment Appeal Panel reviews the information from you and the assessor and makes a decision. A record of the appeal and its outcome is kept.
You will be told the outcome within 2 weeks of lodging the appeal. The panel's decision is final.

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