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Data Analytics with R

Course Information

  • Sessions 2 days
  • Duration 15 hrs
  • Level Beginner
  • Assessment NA

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.

Course Brochure

Download Course Brochure

Prerequisite

This course is for beginners. No prerequisite is required.

Certification

  • 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.

Data Analytics with R

Course Code: C182

147 Review(s) | Add Your Review

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What's This Course About

Data Analytics with R teaches you how to transform raw data into actionable insights using R, the powerful open-source language for statistics and data analysis. Widely used in research, finance, healthcare and business analytics, R offers a rich ecosystem of packages for cleaning, analysing and visualising data. This course is designed for analysts, researchers, students and professionals who want a practical, hands-on introduction to data analytics using R and RStudio.

You will begin with data preparation and transformation, importing data from files and databases, and using the tidyverse, including dplyr and tidyr, to clean, filter, reshape, join and create new variables. Next you will learn to produce data summaries, calculating descriptive statistics and grouping data to compare segments. You will then move into quantitative data analysis, applying techniques such as correlation, hypothesis testing and regression to explore relationships and test assumptions in numeric data.

The course continues with qualitative data analysis, working with categorical and text data, frequency tables and cross-tabulations, followed by data visualisation with ggplot2 to create clear bar charts, histograms, scatter plots and multi-panel charts. Every topic is hands-on with real datasets and reproducible R scripts, and you will learn how to document your analysis with R Markdown. By the end, you will be able to prepare, analyse and visualise data in R confidently and communicate your findings in a way that supports better decisions.

Why Take This Course?

  • Hands-On Learning Learn by doing. Every topic is practised hands-on, so you leave with skills you can use at work straight away.
  • Live Coaching Experienced instructors coach you live, answer your questions and guide you step by step.
  • Free Post-Course Consultation Stuck after class? Message your trainer any time for guidance as you apply what you have learned.
  • Always-Updated Materials Materials are refreshed to stay relevant. Log in to our LMS any time to get the latest version.

Funding Options

No funding is available for this course

For CASL funding, please checkout the details at CASL - Data Analytics and Visualization with R

Course Fee

$700.00 (GST-exclusive)
$763.00 (GST-inclusive)

Course Date

Course Time

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Additional Note

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

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.

Cancellation & Reschedule Policy

  • 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

Course Details

What You'll Learn

Topic 1: Data Preparation and Transformation

Topic 2: Data Summary

Topic 3: Quantitative Data Analysis

Topic 4: Qualitative Data Analysis

Topic 5: Data Visualization

Course Info

Minimum Entry Requirement

Knowledge and Skills

  • Able to operate using computer functions
  • 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.

Target Age Group: 21-65 years old

Minimum Software/Hardware Requirement

Software:

You will need the following for this course:

Hardware: Windows PC or Mac laptop

Job Roles

Job Roles

  • Data Analyst
  • Market Researcher
  • Business Analyst
  • Quality Assurance Specialist
  • Social Science Researcher
  • Graduate Student
  • Economic Analyst
  • Product Manager
  • Human Resources Analyst
  • Healthcare Data Specialist
  • Educational Researcher
  • Sports Statistician
  • Financial Analyst
  • Behavioral Scientist
  • Environmental Data Specialist.

Trainers

Trainers

Dr. Alvin Ang is a data scientist and data science educator with a PhD in Operations Research, an MSc in Logistics and a BEng in Mechatronics, Robotics and Automation Engineering, all from Nanyang Technological University. Operations research is the mathematics of better decisions, and his published work on Kanban production-control systems at IEEE conferences reflects the quantitative rigour he brings to every class. He has served as an IBM Data Science Instructor, a Research Fellow at NUS, a Principal Consultant in data science and an Assistant Professor of Mathematics at SP Jain School of Global Management, where he was named Mathematics Professor of the Year, and he lectured undergraduates in statistics and quantitative methods at SUSS. Since 2021 he has trained professionals at Tertiary Infotech in Python, R, SQL, statistics, Excel analytics, Tableau, Power BI, Apache Spark, machine learning and deep learning, and he founded DataFrens.sg, a community for data scientists in Singapore. An ACLP-certified adult educator, he is known for connecting technical concepts to practical, real-world applications, a strength echoed in hundreds of learner recommendations.

In Data Analytics with R, Dr. Ang teaches data analysis in R, the language he has long used for statistics and research. Learners import, prepare and transform data, summarise it, apply quantitative analysis and statistical tests, and present results with clear visualisations. Having lectured statistics and quantitative methods at university level, he explains each method in plain language and shows how to interpret the output correctly.

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.

Review

Customer Reviews (147)

Engaging Data Analytics with R Course 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 Data Analytics with R course, and I enjoyed the class a lot. Dr Alvin Ang was able to explain R concepts very clearly and answer our questions promptly. His teaching style was very engaging (he includes some witty humour during the class from time to time). I would recommend anybody who wants to learn a skill to come sign up for a course at Tertiary Courses Singapore. (Posted on 8/12/2026)
will recommend 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
. (Posted on 10/17/2024)
will recommend 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 10/17/2024)
will recommend 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 10/16/2024)
will recommend 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 10/16/2024)

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