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Beginner-To-Mastery over Data Visualization Using R (2025)

Name: Beginner-To-Mastery over Data Visualization Using R (2025)
Rating: 4.6 (6 reviews)

Gain Highly In-demand Basic and Advanced Data Visualization Skills using R-Programming, guided by top industry expert

Created byTalent loom, Dr. Nirbhay Mathur

Last updated 1/2025

English

What you'll learn

Master the basics of R Programming like creation and manipulation of logical and operational variables and vectors in R
Gain proficiency in Decision Making Functions such as if-else statements, while loops, do-while loops, and for loops for effective control flow in programming
Learn to construct Handling Matrices & Lists, utilize colnames() and rownames() functions
Explore various data types and work with data frames for structured data management
Learn Importing & Exporting Data such as reading CSV files, importing Excel spreadsheets, and performing data indexing, selection, and web scraping
Utilize dplyr functions to select, filter, arrange, rename parameters, mutate datasets, and summarize data efficiently using %>% pipe operations
Gain insights into the components and structure and anatomy of plots
Use ggplot2 to create advanced visualizations for continuous data, including multiple datasets on one plot, error bars, density plots, and surface plotting
Create effective visualizations for discrete data types such as bar plots and mosaic plots, enhancing data exploration and presentation
Dive into advanced ggplot2 functionalities and techniques
Learn specialized techniques like plotting histograms with continuous and categorical variables, time series heat maps and dendrogram plots
Introduction to clustering techniques like K-means clustering for machine learning applications
Apply acquired skills and knowledge to a comprehensive capstone project, demonstrating proficiency and readiness for practical application
Practice alongside quizzes, exercises, and solution videos to reinforce learning

Course content

15 sections • 69 lectures • 7h 35m total length

Welcome to data visualization course using R8:32
Introduces the course, outlining its goals and the value of learning data visualization using R.
History of R and Data Visualization1:09
Provides a brief history of R and its evolution as a powerful tool for data visualization, highlighting key milestones and developments.
Getting ready with playground (Installing R & R studio -- Windows & Mac)11:01
Guides learners through installing R and RStudio on Windows and Mac, ensuring they have the necessary tools to start their data visualization journey
Live Demo - Wonders to see6:26
Showcases the potential of R with a live demo, inspiring learners by demonstrating impressive data visualization examples.
How to get datasets2:24
Explains how to find and acquire datasets, setting the stage for hands-on practice and learning throughout the course.

Welcome note about this section0:40
Introduces the section's focus on fundamental R programming principles essential for data visualization.
What is Variables3:06
Defines variables and their importance in programming, laying the foundation for data manipulation in R.
Using an Creating Variables7:58
Teaches learners how to create and use variables in R, a critical skill for any data-related task.
Logical and Operational Variables and vectors9:31
Explains the use of logical and operational variables and introduces vectors, a fundamental data structure in R.
vectors in R14:23
Delves deeper into vectors, covering their creation, manipulation, and applications in R programming.
Quiz on R-Principles

Welcome note about this section1:15
Sets the stage for exploring decision-making functions in R, crucial for data analysis.
If loop, If else, If else ladder9:55
Introduces conditional statements, teaching learners how to make decisions based on data conditions.
While loop, Do-while loop8:16
Covers iterative loops, enabling learners to perform repeated actions on data sets.
for loop3:25
Explains the for loop, a powerful tool for iterating over elements in R, with practical examples.
Quiz on Decision Making Functions

Welcome note about this section1:44
Introduces the section's focus on matrices and lists, two key data structures in R.
What is Matrixes1:42
Defines matrices, explaining their structure and importance in data organization and manipulation.
Building your first Matrixes3:19
Guides learners through creating their first matrices, providing hands-on experience.
Colnames () and Rownames () functions10:48
Teaches learners how to use colnames() and rownames() functions to enhance matrix readability.
What is Lists1:35
Introduces lists, a versatile data structure in R, highlighting their use cases and benefits.
Creating lists in R21:56
Provides step-by-step instructions for creating lists, enabling learners to manage diverse data types.
Playing with lists in R6:24
Demonstrates various operations on lists, showcasing their flexibility and power.
Quiz on Matrices and List in R

Welcome note about this section0:50
Introduces the section's focus on different data types in R, essential for effective data analysis.
Different data types in R1:27
Explains the various data types in R, providing a comprehensive overview.
Numeric and Integer data type4:57
Covers numeric and integer data types, highlighting their applications and differences.
Logical data type and Complex data type3:06
Introduces logical and complex data types, explaining their unique features and use cases.
Character data type and Raw data type3:29
Explains character and raw data types, essential for text and raw data handling.
Data frames5:23
Introduces data frames, a crucial data structure in R, explaining their creation and manipulation.
Quiz on Data types in R

Welcome note about this section2:01
Sets the stage for learning how to import and export data in R, a critical skill for data analysis.
Reading CSV files in R6:53
Teaches learners how to read CSV files into R, a common data import method.
Importing Excels4:13
Covers importing Excel files, expanding learners' ability to work with different data formats.
Data set indexing and selection15:27
Explains how to index and select data from datasets, enabling precise data manipulation.
Data base9:53
Introduces working with databases in R, providing a gateway to more advanced data management.
Web scraping22:41
Teaches learners the basics of web scraping, a valuable skill for acquiring online data.

Welcome note about this section1:52
Introduces the section's focus on using the dplyr package for data manipulation.
Select from data set13:54
Teaches learners how to select specific columns from a dataset using dplyr.
Filter from data set8:11
Covers filtering data based on conditions, a powerful tool for data analysis.
Arrange from data set1:55
Explains how to arrange data in a desired order, enhancing data organization.
Rename dataset parameters3:10
Shows how to rename columns in a dataset, improving data readability.
Mutate from data set7:42
Teaches learners how to create new variables or modify existing ones.
Summarize dataset7:29
Covers summarizing data, providing a concise overview of key metrics.
Create %>% pipe operations6:31
Introduces the pipe operator, a key feature in dplyr for chaining operations.

Welcome13:53
Sets the stage for intermediate plotting techniques using continuous data.
Continuous Data - Multiple dataset on one plot7:40
Teaches learners how to plot multiple datasets on a single plot, enhancing comparative analysis.
Continuous Data - Error bars3:07
Covers adding error bars to plots, providing insights into data variability.
Continuous Data - Density Plots2:11
Introduces density plots, a powerful tool for visualizing data distribution.
Continuous Data - Plotting a surface2:47
Teaches learners how to create surface plots, providing a 3D perspective on data.
Quiz on plotting

Requirements

No prior experience is required. We will start from the very basics

Description

Learning Outcomes You Can Expect!

This course is designed for professionals from varied industries to be able to:

Advance in their careers with enhanced data visualization skills opening doors to promotions and new opportunities.

Become a data storyteller who can weave complex data into compelling narratives. Your ability to present data visually will help you make a lasting impression in every presentation.

Gain mastery in operating within the R Programming language environment.

Develop the ability to master the following charts and plots that resonate with your audience:

Bar chart

Pie chart

Stacked area chart

Line chart

Histogram

Scatter plot

Mosaic Plot

Scatter plot with a trendline (regression plot)

Dendrogram plot

Bubble plot

Distribution plot

Correlogram plot

Clustering plot

Effectively display categorical data and highlight relationships between variables, making your visualizations both informative and visually appealing.

Explore the potential of ggplot2 to create advanced and highly customizable data visualizations, including histograms, scatter plots, bar plots, box plots, and area charts.

Dive into advanced visualization techniques such as creating time series heatmaps, a powerful tool for visualizing data trends over time, and employing clustering techniques like K-means to uncover patterns in your data.

Build an Impressive Portfolio by putting your newfound skills to the test across the whole course. Apply your learnings to a real-world dataset, creating a comprehensive project that you can showcase in your professional portfolio.

What makes this course more effective?

Hands-on Learning: You will master data visualization skills through practical exercises and projects integrated throughout the course. This hands-on approach ensures you can apply theoretical knowledge to real-world scenarios effectively.

Experienced Trainer: Learn from industry experts like Nirbhay, who are not only passionate about data visualization and R programming but also bring a wealth of real-world experience to the classroom. Nirbhay’s expertise ensures you gain insights from someone who knows the industry inside and out.

Well-Structured Content: Our curriculum is meticulously designed for optimal learning. It begins with foundational concepts and progressively advances to more complex topics, ensuring a comprehensive understanding of data visualization.

Latest Industry Updates: Stay ahead of the curve by learning the latest insights, techniques, and trends in data visualization. Our course content is regularly updated to reflect the newest developments in the field, preparing you for both current and future industry demands.

Capstone Project: Put your skills to the test with a real-world data visualization challenge. This capstone project allows you to apply what you’ve learned in a practical setting, giving you a taste of real industry work and enhancing your portfolio.

Who exactly benefits from this course?

Data visualization with R is an indispensable skill for data analysts and aspirants, enabling them to transform complex datasets into comprehensible graphical representations.
However, its utility extends far beyond this group, empowering any professional tasked with presenting data in a visually compelling manner.

In the finance sector, the R programming language excels in rendering intricate financial data accessible to both domain experts and stakeholders.

Marketers harness R to generate visually intuitive insights that drive strategic decisions, enhancing their ability to navigate market dynamics. Operations teams leverage R to develop user-friendly dashboards that streamline workflows and facilitate informed decision-making processes. In the medical field, R plays a transformative role in converting patient data and treatment outcomes into insightful visualizations, a capability that proved especially critical in the real-time tracking and analysis of COVID-19 data.

R's data visualization capabilities also extend to education, retail, and government sectors.

In Education, R simplifies the presentation of student performance metrics. Retail professionals use it to illustrate sales trends and patterns effectively. Government agencies rely on R for elucidating public health data and other critical information, making complex datasets accessible to the public and policymakers alike.

Mastering data visualization with R equips professionals to communicate data with clarity and impact, driving meaningful decisions across any industry. If you’re poised to elevate your career, our comprehensive course offers a meticulously structured journey from fundamental concepts to advanced techniques.

Experience extensive hands-on activities, engage in a robust Capstone Project, and benefit from the guidance of industry-leading experts. By the end of this course, you’ll be proficient in tackling real-world challenges with confidence.

Seize the opportunity to unlock the full potential of data visualization with R.

Get to know your Trainer!

Dr. Nirbhay Mathur is a distinguished data scientist and AI expert with over nine years of experience working with top global firms. Holding a Ph.D. in Predictive Maintenance, his expertise encompasses Data Visualization, Data Analysis, Reliability, Computer Vision and LLM. Renowned for simplifying complex technical concepts, Dr. Mathur excels in problem-solving and innovation.

Dr Nirbhay remains at the cutting edge of data science, integrating current best practices and emerging trends into his work. His research interests span data processing, machine learning, and predictive analytics. Passionate about teaching, he makes intricate topics engaging and accessible, inspiring a deeper appreciation for the field among his students.

Dr Nirbhay's deep industry knowledge and forward-thinking approach make him an exceptional trainer for learning data visualization. His commitment to continuous learning and professional development ensures that his students receive the most up-to-date and relevant information available.

He aims to inspire the next generation of engineers and data scientists by sharing his extensive knowledge and enthusiasm for the field. With Dr Nirbhay as your instructor, you can expect a learning experience that is not only informative but also inspiring, enriching, and thought-provoking.

Who this course is for:

Beginners with No Prior R Programming Language Experience: We'll guide you step-by-step through R basics and data visualization concepts
Data Enthusiasts: Enhance your ability to analyze and interpret data through visual storytelling
Analysts Seeking to Level Up: Take your data visualization skills to the next level with advanced techniques and R packages
Business Analysts: Learn how to effectively communicate data insights to stakeholders using data visualizations
Marketing Professionals: Gain the skills to create data-driven marketing campaigns and presentations
Data Scientists: Expand your data science toolkit with data visualization capabilities
Students pursuing Data Analytics or Statistics programs: Build a strong foundation in data visualization using R
Anyone eager to communicate data insights effectively: Learn how to transform raw data into clear and impactful visuals

Beginner-To-Mastery over Data Visualization Using R (2025)

What you'll learn

Explore related topics

Course content

Welcome and get ready5 lectures • 30min

Understanding R Programing Principles5 lectures • 36min

Decision Making functions4 lectures • 23min

Handling Matrices & Lists in R7 lectures • 47min

Understanding Data in R6 lectures • 19min

Importing & Exporting Data in R6 lectures • 1hr 1min

Data Frame with "dplyr"8 lectures • 51min

Understanding Anatomy of plot1 lecture • 9min

Data Visualization using Continuous Data - Intermediate Plotting5 lectures • 30min

Data Visualization using Discrete Data - Intermediate Plotting3 lectures • 12min

Requirements

Description

Who this course is for: