Data Analysis with Shiny: R Playbook from Pluralsight

R Shiny is the answer to a data scientist’s difficulty in deploying their projects to their organization. In this course, you will learn how to use the Shiny package in R to develop and deploy a data science project that may be consumed by the organization.

When it comes to generating value for the organization with data science projects, many data scientists face a key problem in the deployment of these projects. R Shiny is a package in R that solves this deployment problem by creating easy-to-use web applications in R.

In this course, Data Analysis with Shiny: R Playbook, you will learn foundational knowledge of the R Shiny package in R programming.

First, you will learn the background of R Shiny’s purpose in solving the deployment obstacle in data science.

Next, you will discover how R Shiny uses reactive environments and simple R elements to create a seamless app.

Finally, you will explore how to deploy a Shiny app into a cloud hosted site on Shinyapps.io.

When you are finished with this course, you will have the skills and knowledge of R Shiny needed to deploy a data science project into the organization. Software required: R programming and R Studio

What's inside

Syllabus

Course Overview

Up and Running with Shiny

Setting up the Shiny App

Customizing Shiny App

Deploy Shiny App

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Course targets data scientists who need to deploy their projects for organizational consumption

Instruction provided by Jacey Heuer, a recognized instructor

In-demand skills taught, which are relevant in industry

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Data Analysis with Shiny: R Playbook with these activities:

Review R Programming Basics

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Refreshing your R programming knowledge will strengthen the foundation for learning Shiny app development.

Browse courses on R Programming

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Review online resources or books on R programming fundamentals.
Practice writing basic R code to refresh your syntax and data manipulation skills.
Complete practice exercises or online quizzes to test your understanding.

Join Online Communities for Data Science and R Programming

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Connecting with professionals in the field can broaden your network and provide valuable insights.

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Join online communities like RStudio Community or DataCamp.
Introduce yourself and engage in discussions related to Shiny app development.
Learn from others, share your knowledge, and stay updated on industry trends.

Review 'Shiny for R' by Winston Chang

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This book provides a comprehensive overview of Shiny app development, complementing the course material.

View R Graphics Cookbook: Practical Recipes for... on Amazon

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Read the book and focus on chapters relevant to the topics covered in the course.
Take notes and highlight important concepts.
Consider completing the exercises provided in the book.

Six other activities

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Assist Fellow Students with Shiny App Development

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Mentoring others can solidify your own understanding of the concepts and foster a collaborative learning environment.

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Offer assistance to fellow students in the course or online forums.
Answer questions and provide guidance on Shiny app development.
Share your own experiences and best practices.

Explore Additional R Shiny Resources

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Reviewing online tutorials and documentation will supplement the course material and provide additional insights.

Browse courses on R Shiny

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Visit the official R Shiny documentation.
Search for tutorials on YouTube or other online learning platforms.
Explore examples and case studies of Shiny apps.

Practice Interactive Coding Challenges

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Practicing coding challenges will reinforce the concepts learned in the course and strengthen your programming skills.

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Solve interactive coding challenges on platforms like HackerRank or LeetCode.
Focus on challenges related to R programming and data visualization.
Debug your code and seek assistance from online forums or the course instructor when needed.

Attend Online Workshops on Shiny App Development

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Participating in workshops can provide hands-on experience and networking opportunities to enhance your learning.

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Search for online workshops or meetups focused on Shiny app development.
Register for the workshop and prepare any necessary materials.
Actively participate in the workshop, ask questions, and engage with other attendees.
Apply the knowledge and skills gained in the workshop to your own projects.

Develop a Shiny App for a Specific Project

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Creating a Shiny app for a practical project will apply the skills learned in the course and demonstrate your understanding.

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Identify a real-world problem or dataset that can be visualized using a Shiny app.
Design the user interface and functionality of the app.
Write the R code to implement the app's logic and visualization.
Deploy the app to a hosting platform like Shinyapps.io.
Share your app with others for feedback and improvement.

Deploy a Shiny App to a Public Platform

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Deploying a Shiny app publicly showcases your skills and allows others to interact with your work.

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Choose a suitable Shiny app that you have developed.
Select a hosting platform like Shinyapps.io or Heroku.
Deploy your app to the platform and make it publicly accessible.
Share the link to your deployed app with others.

Career center

Learners who complete Data Analysis with Shiny: R Playbook will develop knowledge and skills that may be useful to these careers:

Web Developer

As a Web Developer, you will be able to deploy web apps that you create using the R programming language. You will learn how to design responsive web apps that can be shared and accessed through a web browser. In addition, you will be able to customize your web apps by adding interactive features and dashboards.

See salaries and explore the career path for Web Developer

Data Scientist

As a Data Scientist, you will be able to use R Shiny to develop and deploy machine learning models. This will allow you to create predictive models that can be used to make informed decisions and drive business outcomes.

See salaries and explore the career path for Data Scientist

Statistician

As a Statistician, you will be able to use R Shiny to create interactive statistical reports and visualizations. This will allow you to communicate your findings in a way that is easy for others to understand and make informed decisions.

See salaries and explore the career path for Statistician

Data Analyst

As a Data Analyst, you will be able to use R Shiny to create interactive data visualizations and dashboards. This will allow you to present your data in a way that is easy for others to understand and make informed decisions.

See salaries and explore the career path for Data Analyst

Product Manager

As a Product Manager, you will be able to use R Shiny to create interactive prototypes and demos of your products. This will allow you to get feedback from users and stakeholders early in the development process.

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Software Engineer

As a Software Engineer specializing in data science, you will have the skills to develop and deploy R Shiny applications. This will allow you to create web-based data products that can be used by a wide range of users.

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Financial Analyst

As a Financial Analyst, you will be able to use R Shiny to create interactive financial models and reports. This will allow you to analyze financial data and make informed decisions about investments and other financial matters.

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Business Analyst

As a Business Analyst, you will be able to use R Shiny to create interactive reports and dashboards. This will allow you to present your findings in a way that is easy for others to understand and make informed decisions.

See salaries and explore the career path for Business Analyst

Marketing Analyst

As a Marketing Analyst, you will be able to use R Shiny to create interactive marketing campaigns and reports. This will allow you to track the success of your campaigns and make informed decisions about future marketing activities.

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Consultant

As a Consultant, you will be able to use R Shiny to create interactive presentations and demos. This will allow you to communicate your findings and recommendations to clients in a way that is easy for them to understand and act on.

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Data Engineer

As a Data Engineer, you will be able to use R Shiny to create interactive dashboards and visualizations of your data pipelines. This will allow you to monitor the performance of your pipelines and make informed decisions about how to improve them.

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UX Designer

As a UX Designer, you will be able to use R Shiny to create interactive prototypes and demos of your designs. This will allow you to get feedback from users and stakeholders early in the design process.

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Machine Learning Engineer

As a Machine Learning Engineer, you will be able to use R Shiny to create interactive dashboards and visualizations of your machine learning models. This will allow you to monitor the performance of your models and make informed decisions about how to improve them.

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Educator

As an Educator, you will be able to use R Shiny to create interactive lessons and demonstrations. This will allow you to engage your students and make learning more fun and effective.

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Research Scientist

As a Research Scientist, you will be able to use R Shiny to create interactive presentations and demos of your research findings. This will allow you to communicate your findings to other researchers and stakeholders in a way that is easy for them to understand and build upon.

See salaries and explore the career path for Research Scientist