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R Data Visualization Training in Singapore

Course Information

  • Sessions 1 day
  • Duration 7.5 hrs
  • Level Intermediate
  • 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.

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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.

Data Visualisation with R Training

Course Code: C398

9 Review(s) | Add Your Review

What's This Course About

Embark on a transformative journey into the realm of data visualization with "Data Visualisation with R Training". R, a versatile statistical programming language, offers a broad array of tools and libraries for crafting insightful visual narratives from data. Our course takes participants from the rudiments of creating basic plots in R to the advanced realms of ggplot2, unveiling the potential of data visualization in the R ecosystem.

Dive deeper into the world of ggplot2, understanding its core components, and exploring its customization capabilities. Learn the art of data piping and seamlessly integrate Google Map API using ggmap for geospatial visualizations. As data becomes the new currency, mastering R-based visualization techniques stands paramount. With hands-on examples and immersive sessions, participants will emerge from this course ready to turn data into visually compelling stories that captivate and inform.

Funding Options

No funding is available for this course

Course Fee

$350.00 (GST-exclusive)
$381.50 (GST-inclusive)

Course Date

Course Time

* Required Fields

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: Overview of Basic Plots in R

Scatter and Bubble Plots

Partition Plots

Bar Plot

Histogram

Pie Chart

Box Plot

Heatmap

Treemap

3D plots

Topic 2: Data Visualization with ggplot2

What is ggplot2

Components of ggplot2

Scatter Plot

Add Attributes to Aesthetics

Add Smoothing Line

Bar Plot

Histogram

Box Plot

Data Piping

Topic 3: Customize Visualization

Modifying Background

Modify Axis, Limits and Legend

Annotation and Titles

Add Reference Lines

Pre-Built Themes

Install Additional Themes

Topic 4: New Topic

Google Map API

Install ggmap

Get Google Map

Get Geo Coding

Plot Points on Map

Add Text to Map

Modifying Points on Map

Course Info

Prerequisite

The following knowledge is assumed

Software Requirement

Please download and install the following software prior to the class

Job Roles

Job Roles

  • Data analysts
  • Financial analysts
  • Marketers
  • Researchers

Trainers

Trainers

Dwight Nuwan Fonseka

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.

Richard Wan

Richard Wan is an ACLP-certified lecturer and software consultant with over 40 years of experience in software and hardware development, spanning AI, computer vision, and machine learning. He began his programming career with 8-bit computing in the late 1970s and went on to earn his M.Sc. in Electrical Engineering (Computer Vision) from the University of Wisconsin–Madison. His professional contributions include co-founding multiple high-tech companies, pioneering digital publishing technologies, and leading AI-driven software development in healthcare, defense, and manufacturing.

Richard has taught a wide range of technical courses, including machine learning with Scikit-Learn, deep learning with TensorFlow and PyTorch, and computer vision with OpenCV. In predictive analytics, he emphasizes the use of PyTorch for building deep learning models that can forecast trends, detect anomalies, and classify outcomes. His teaching approach blends decades of hands-on development with structured, beginner-friendly instruction, equipping learners with practical skills to transform data into prediction.

Review

Customer Reviews (9)

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
Nil (Posted on 5/21/2018)
Might 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
The agenda is well structured and the content is good. It would be better if this is 2 day course with more hands on practice.

The lecturer is friendly and passionate about the subject, and the quiet environment is excellent for the class (Posted on 2/26/2018)
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
Weekend is better for me. For today, i have to use my annual leave. Even i want to attend some courses, weekdays are not good for me. (Posted on 12/12/2017)
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
May wish to consider putting together all the visualization plots and create a gallery for the course promotional materials

Can send participants the list of packages to install in advance to save on downloading and installing time (Posted on 8/28/2017)

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