Coursera

Publishing Visualizations in R with Shiny and flexdashboard (Coursera)

Offered by Johns Hopkins University,
Publishing Visualizations in R with Shiny and flexdashboard (Coursera)

This course is the fourth in the Specialization "Data Visualization and Dashboarding in R." Learners will come to this course with a strong background in making visualization in R using ggplot2. To build on those skills, this course covers creating interactive visualization using Shiny, as well as combining different kinds of figures made in R into interactive dashboards. Data visualization is a critical skill for anyone that routinely using quantitative data in his or her work - which is to say that data visualization is a tool that almost every worker needs today.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

One of the critical tools for data visualization today is the R statistical programming language. Especially in conjunction with the tidyverse software packages, R has become an extremely powerful and flexible platform for making figures, tables, and reproducible reports. However, R can be intimidating for first time users, and there are so many resources online that it can be difficult to sort through without guidance.

Course 4 of 5 in the Data Visualization & Dashboarding with R Specialization

Syllabus

WEEK 1
Introduction to Shiny
In this module, we will get started using Shiny to create interactive visualizations. You should begin by watching the introductory videos in each lesson. Then, carefully review the readings and reference materials provided. Once you have done that, I recommend watching the videos again to check your understanding. You will take a few quizzes as you progress through the material to make sure you are keeping up.

WEEK 2
Customizing Shiny Apps
In this module, we will go into greater details about laying Shiny applications. You should begin by watching the introductory videos in each lesson. Then, carefully review the readings and reference materials provided. Once you have done that, I recommend watching the videos again to check your understanding. You will take a few quizzes as you progress through the material to make sure you are keeping up.

WEEK 3
flexdashboard
In this module, we will learn how to use flexdashboard to display visualization in a dashboard format. You should begin by watching the introductory videos in each lesson. Then, carefully review the readings and reference materials provided. Once you have done that, I recommend watching the videos again to check your understanding. You will take a few quizzes as you progress through the material to make sure you are keeping up.

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Introduction to Statistics (Coursera) Coursera
Stanford University

Introduction to Statistics (Coursera)

Statistics & Data Analysis Data Science

Stanford's "Introduction to Statistics" teaches you statistical thinking concepts that are essential for learning from data and communicating insights. By the end of the course, you will be able to perform exploratory data analysis, understand key principles of sampling, and select appropriate tests of significance for multiple contexts. You will gain the foundational skills that prepare you to pursue more advanced topics in statistical thinking and machine learning.

Nov 2nd 2026
5-12 Weeks
Statistics Analysis Probability
Details
Basic Statistics (Coursera) Coursera
University of Amsterdam

Basic Statistics (Coursera)

Statistics & Data Analysis Data Science

Understanding statistics is essential to understand research in the social and behavioral sciences. In this course you will learn the basics of statistics; not just how to calculate them, but also how to evaluate them. This course will also prepare you for the next course in the specialization - the course Inferential Statistics. In the first part of the course we will discuss methods of descriptive statistics. You will learn what cases and variables are and how you can compute measures of central tendency (mean, median and mode) and dispersion (standard deviation and variance). Next, we discuss how to assess relationships between variables, and we introduce the concepts correlation and regression.

Oct 26th 2026
5-12 Weeks
Statistics Probability Regression
Details
Population Health: Responsible Data Analysis (Coursera) Coursera
Leiden University

Population Health: Responsible Data Analysis (Coursera)

Statistics & Data Analysis Data Science

In most areas of health, data is being used to make important decisions. As a health population manager, you will have the opportunity to use data to answer interesting questions. In this course, we will discuss data analysis from a responsible perspective, which will help you to extract useful information from data and enlarge your knowledge about specific aspects of interest of the population.

Nov 2nd 2026
4 Weeks
Data Analysis R Programming Regression Analysis
Details
Data science perspectives on pandemic management (Coursera) Coursera
Politecnico di Milano

Data science perspectives on pandemic management (Coursera)

Statistics & Data Analysis Data Science

The COVID-19 pandemic is one of the first world-wide scenarios where data made a difference in capturing and analyzing the diffusion and impact of the disease. We offer an introductory course for decision makers, policy makers, public bodies, NGOs, and private organizations about methods, tools, and experiences on the use of data for managing current and future pandemic scenarios.

Nov 2nd 2026
5-12 Weeks
Gamification Data Analysis Data Science
Details
Supply Chain Analytics Essentials (Coursera) Coursera
Rutgers University

Supply Chain Analytics Essentials (Coursera)

Business

In this introductory course to Supply Chain Analytics, I will take you on a journey to this fascinating area where supply chain management meets data analytics. You will learn real life examples on how analytics can be applied to various domains of a supply chain, from selling, to logistics, production and sourcing, to generate a significant social / economic impact.

Nov 2nd 2026
4 Weeks
Data Analysis Supply Chain Supply Chain Analytics
Details
Programming Languages, Part A (Coursera) Coursera
University of Washington

Programming Languages, Part A (Coursera)

CS: Software Engineering CS: Programming

This course is an introduction to the basic concepts of programming languages, with a strong emphasis on functional programming. The course uses the languages ML, Racket, and Ruby as vehicles for teaching the concepts, but the real intent is to teach enough about how any language “fits together” to make you more effective programming in any language -- and in learning new ones.

Nov 2nd 2026
5-12 Weeks
Programming Java ML
Details
Introducción a Java (Coursera) Coursera
Universidad Nacional Autónoma de México

Introducción a Java (Coursera)

CS: Programming

Me llamo Elisa Viso y una de mis pasiones es la de programar y enseñar a programar. El lenguaje Java es uno de los que más me ha gustado en mis 45 años que llevo programando. Si bien te podrá parecer un poco complicado empezar a programar en Java, una vez que cubras los conceptos básicos verás qué rápido se avanza. Java, como todos los lenguajes de programación bien hechos, te dejan hacer cualquier cosa (algunas de ellas con más trabajo que en otros lenguajes y otras casi directamente de cómo piensas la solución al problema).

Nov 2nd 2026
5-12 Weeks
Programming Java Java Programming
Details
Ferramentas para Ciência de Dados: Introdução ao R (Coursera) Coursera
FIA Business School

Ferramentas para Ciência de Dados: Introdução ao R (Coursera)

Statistics & Data Analysis

Nossas boas-vindas ao Curso Ferramentas para Ciência de Dados: Introdução ao R. Neste curso, você aprenderá que o mundo evoluiu muito quando o assunto é tomada de decisão baseada em dados e já não é possível comparar a quantidade de informações a que temos acesso atualmente com o que tínhamos disponíveis décadas atrás.

Nov 2nd 2026
4 Weeks
Data Science R Language R Programming
Details
Making Data Science Work for Clinical Reporting (Coursera) Coursera
Genentech

Making Data Science Work for Clinical Reporting (Coursera)

Statistics & Data Analysis Data Science

This course is aimed to demonstrate how principles and methods from data science can be applied in clinical reporting. By the end of the course, learners will understand what requirements there are in reporting clinical trials, and how they impact on how data science is used. The learner will see how they can work efficiently and effectively while still ensuring that they meet the needed standards.

Nov 2nd 2026
4 Weeks
Github Clinical Trials Data Science
Details
Programming Fundamentals (Coursera) Coursera
Duke University

Programming Fundamentals (Coursera)

CS: Theory CS: Programming

Programming is an increasingly important skill, whether you aspire to a career in software development, or in other fields. This course is the first in the specialization Introduction to Programming in C, but its lessons extend to any language you might want to learn. This is because programming is fundamentally about figuring out how to solve a class of problems and writing the algorithm, a clear set of steps to solve any problem in its class.

Nov 2nd 2026
4 Weeks
Programming Algorithms C Language
Details
Python Data Visualization (Coursera) Coursera
Rice University

Python Data Visualization (Coursera)

CS: Software Engineering CS: Programming

This if the final course in the specialization which builds upon the knowledge learned in Python Programming Essentials, Python Data Representations, and Python Data Analysis. We will learn how to install external packages for use within Python, acquire data from sources on the Web, and then we will clean, process, analyze, and visualize that data. This course will combine the skills learned throughout the specialization to enable you to write interesting, practical, and useful programs.

Oct 30th 2026
4 Weeks
Programming Python Scripting
Details