EdX

RShiny for Everyone (edX)

RShiny for Everyone (edX)

Use R’s Shiny package to create data-driven, interactive web applications. In this course, you will use R Shiny to create an interactive web application that highlights the biodiversity of America’s National Parks. Your application will feature an interactive map, biodiversity calculator, trail journal and species images. Using R Shiny, you will expand your data analysis and visualization skills while developing your workflow through web application deployment.

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

If you are a beginner level data professional, a student, a researcher, an academic marketing analyst, business and data analyst, or financial analyst, this course is for you.
This four week course will give you a foundation for making and deploying Shiny applications. Along the way you will learn about user interaction (UI) controls, persistent data storage using google sheets, customizing your application with CSS and deployment through shinyapps.io. You will create your own unique application(s) that you can share with friends, colleagues, and potential employers.
This course is part of the Web App Development for Data Scientists Professional Certificate.

What you'll learn

  • Structuring an application using shinydashboard
  • Creating interactive visualizations, maps, and specific UI components
  • Storing data using the Google Sheets API

Syllabus

This course is meant to teach the basics of building an app using RShiny. It presents a general introduction to the capabilities of RShiny with a particular focus on "learning by doing." At the end of each week of instruction, you'll complete a "wrap-up exercise" and quiz that reinforce the techniques you've learned.

Week 1

  • Getting Set Up
  • Using R Studio IDE for Shiny
  • Basic UI
  • Client Side vs Server Side Components

Week 2

  • Server Side UI
  • Leaflet Maps
  • Server Side Outputs
  • Buttons, Modal Viewers and Observe Events

Week 3

  • Working with Data
  • The Reactive and Browser Functions
  • Customizing Your App with consideration of CSS Rules and Custom Skins
  • Deploying Your Application!

Week 4

  • Setting Things Up - Where to Begin
  • Starting a New Project
  • Filters for Interactivity
  • Maps and Journals
  • Final Projects!
Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Storytelling and Persuading using Data and Digital Technologies (edX) EdX
University of Maryland, College Park,University System of Maryland - USM,USMx,UMD

Storytelling and Persuading using Data and Digital Technologies (edX)

Learn how to gain traction for your digital transformation initiatives with stories based on data that use compelling data visualizations to build a persuasive business case. Decisions made by humans are rarely made by data alone. Human decision-makers have cognitive biases, are affected by emotions, and make conceptual leaps beyond what the data may suggest.

Self Paced
Self-Paced
Data Processing and Analysis with Excel (edX) EdX
Rochester Institute of Technology,RITx

Data Processing and Analysis with Excel (edX)

Learn to use Excel to organize and clean data so it can be manipulated and analyzed. In this course, you will learn how to organize your data within the Microsoft Office Excel software tool. Once organized, we will discuss data cleaning. You will learn how to identify outliers and anomalies in the data, and how to identify and change data-types. Together we will develop a data analysis plan, after which we will apply analysis methods and tools, including exploratory analysis, evaluation of results, and comparison with other findings.

Self Paced
Self-Paced
Análisis de datos empresariales con R (edX) EdX
Universidad Anáhuac,AnahuacX

Análisis de datos empresariales con R (edX)

Analiza los datos con R y R Studio aplicando nuevas técnicas para tomar decisiones orientadas a los negocios, contemplando información de diversas variables simultáneamente y sé parte de la transformación empresarial. Si tomas decisiones en tu empresa o deseas involucrarte en la ciencia de datos y el uso de tecnologías computacionales, este curso es para ti.

Self Paced
Self-Paced
Excel for Everyone: Core Foundations (edX) EdX
The University of British Columbia,UBCx

Excel for Everyone: Core Foundations (edX)

Learn Excel fundamentals including data wrangling, spreadsheet management, and basic data analysis. This introductory Excel course will equip you with a strong foundational knowledge of Excel to organize, analyze and work with data. You will develop essential Excel skills, such as simple data wrangling and managing spreadsheets, along with a foundational understanding of business data analysis.

Self Paced
Self-Paced
Introduction to Digital Humanities (edX) EdX
HarvardX,Harvard University

Introduction to Digital Humanities (edX)

Develop skills in digital research and visualization techniques across subjects and fields within the humanities. This course will show you how to manage the many aspects of digital humanities research and scholarship. Whether you are a student or scholar, librarian or archivist, museum curator or public historian — or just plain curious — this course will help you bring your area of study or interest to new life using digital tools.

Self Paced
Self-Paced
Case Studies in Functional Genomics (edX) EdX
HarvardX,Harvard University

Case Studies in Functional Genomics (edX)

Perform RNA-Seq, ChIP-Seq, and DNA methylation data analyses, using open source software, including R and Bioconductor. We will explain how to perform the standard processing and normalization steps, starting with raw data, to get to the point where one can investigate relevant biological questions.

Self Paced
Self-Paced
Datos para la efectividad de las políticas públicas (edX) EdX
Inter-American Development Bank - IDB,IDBx

Datos para la efectividad de las políticas públicas (edX)

Este curso te ayudará a tomar el control de los datos y familiarizarte con las herramientas para utilizarlos en la planificación, gestión y evaluación de políticas publicas. En esta era de la información, los datos están disponibles en todos lados y crecen a una tasa exponencial. ¿Cómo podemos darles sentido a todos los datos y aprovecharlos en el momento de tomar decisiones?, ¿cómo los utilizamos para que nos ayuden a guiar la gestión y planificación de nuestras políticas? Tanto si eres ciudadano como planificador de políticas, deberías poder responder a estas preguntas.

Self Paced
Self-Paced
Data Science Tools (edX) EdX
IBM

Data Science Tools (edX)

Learn about the most popular data science tools, including how to use them and what their features are. In this course, you'll learn about Data Science tools like Jupyter Notebooks, RStudio IDE, and Watson Studio. You will learn what each tool is used for, what programming languages they can execute, their features and limitations and how data scientists use these tools today.

Self Paced
Self-Paced
Analyzing Data with R (edX) EdX
IBM

Analyzing Data with R (edX)

R is the key that opens the door between the problems you want to solve with data and the answers you need. This course walks you through the process of answering questions through data. The R programming language is purpose-built for data analysis. R is the key that opens the door between the problems you want to solve with data and the answers you need to meet your objectives.

Self Paced
Self-Paced
Advanced Statistical Inference and Modelling Using R (edX) EdX
University of Canterbury,UCx

Advanced Statistical Inference and Modelling Using R (edX)

Extend your knowledge of linear regression to the situations where the response variable is binary, a count, or categorical as well as to hierarchical experimental set-up. Advanced Statistical Inference and Modelling Using R is part two of the Statistical Analysis in R professional certificate. This course is directed at people who are already familiar with basic linear regression and fundamentals of statistical inference. It extends the knowledge of linear regression to the situations where the response variable is binary, a count, or categorical as well as to hierarchical experimental set-up.

Self Paced
Self-Paced