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Dr. Nikunj Maheshwari
By the end of this project, you will learn how to create a web-based application to view and analyse your dataset using RShiny, a free, open-source R library that you can download. You will learn how reactive programming works between the user interface (UI) and the server. You will then learn how to create a real world web-based application to upload your dataset in CSV format, and view and extract summary information from the dataset. Lastly, you will learn how to dynamically create high quality plots from different columns in your dataset and download these plots for business use.
An RShiny web application is a dynamic...
Read more
By the end of this project, you will learn how to create a web-based application to view and analyse your dataset using RShiny, a free, open-source R library that you can download. You will learn how reactive programming works between the user interface (UI) and the server. You will then learn how to create a real world web-based application to upload your dataset in CSV format, and view and extract summary information from the dataset. Lastly, you will learn how to dynamically create high quality plots from different columns in your dataset and download these plots for business use.
An RShiny web application is a dynamic...
Read more
By the end of this project, you will learn how to create a web-based application to view and analyse your dataset using RShiny, a free, open-source R library that you can download. You will learn how reactive programming works between the user interface (UI) and the server. You will then learn how to create a real world web-based application to upload your dataset in CSV format, and view and extract summary information from the dataset. Lastly, you will learn how to dynamically create high quality plots from different columns in your dataset and download these plots for business use.
An RShiny web application is a dynamic application that updates automatically when the user input changes or updates. These web applications can save you time and resources while speeding up the processes and analysis.
Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
Register for this course and see more details by visiting:
OpenCourser.com/course/1aezkv/creating
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Guides students through the practical stages of uploading, viewing, and extracting data from CSV files
Covers dynamic web-based applications, a high-utility skill in today's tech industry
Helps students understand reactive programming between the user interface (UI) and the server
Involves working with RShiny, a popular open-source R library utilized by data analysts and scientists
Suitable for learners based in North America, with plans for expansion to other regions
Save this course
Save Creating a Dynamic Web Application using RShiny to your list so you can find it easily later:
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Reviews summary
Rshiny web development
Creating a Dynamic Web Application using RShiny provides a detailed look at the creation of web-based applications for data analysis that dynamically update as user input changes. Many reviewers noted that the course may be geared more towards individuals based in North America, but noted that its hands-on approach taught them valuable skills.
Engaging hands-on project.
"on point , hands on project are always fun"
Access to course content may require additional payment.
"after a few days I have tried to review the material, and my surprise is that it asks me to pay again to be able to review the material."
Course materials may be regionally limited.
"Note: This course works best for learners who are based in the North America region."
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 Creating a Dynamic Web Application using RShiny with these
activities:
Read Advanced R
Show steps
This book provides an in-depth look at the R programming language, covering topics such as data manipulation, statistical modeling, and ggplot2.
View
R Packages
on Amazon
Show steps
-
Read the book
-
Work through the exercises in the book
-
Apply what you've learned to your own projects
Review JavaScript Basics
Show steps
Refresh your memory on basic JavaScript syntax and concepts to enhance your understanding of the course material.
Browse courses on
JavaScript
Show steps
-
Read through online tutorials or documentation on JavaScript
-
Complete coding exercises on platforms like Codecademy or LeetCode
Brush up on introductory programming concepts
Show steps
Reviewing the basics of programming can help strengthen your understanding of RShiny, a key component of this course.
Browse courses on
R Programming
Show steps
-
Read through online tutorials or documentation on R programming fundamentals.
-
Complete a few practice exercises or coding challenges to reinforce your understanding.
12 other activities
Expand to see all activities and additional details
Show all 15 activities
Review R basics
Show steps
Review the basics of R, including data structures, functions, and basic statistical analysis. This will help you hit the ground running when you start the course.
Browse courses on
R
Show steps
-
Review the R documentation
-
Complete a few R tutorials
-
Practice writing your own R code
Meet with other RShiny users
Show steps
Meet with other RShiny users to learn from their experiences and share your own. This will help you to expand your network and stay up-to-date on the latest trends in RShiny development.
Show steps
-
Attend a RShiny meetup or conference
-
Join the RShiny community on GitHub
-
Connect with other RShiny users on social media
Attend a RShiny workshop
Show steps
Attend a workshop on RShiny to learn from experts and get hands-on experience.
Show steps
-
Find a RShiny workshop in your area
-
Register for the workshop
-
Attend the workshop
Follow along with RShiny tutorials
Show steps
Engaging with guided tutorials can provide hands-on practice and deepen your understanding of RShiny's capabilities.
Show steps
-
Find online tutorials or courses that cover the fundamentals of RShiny.
-
Work through the tutorials, following the instructions and completing the exercises.
-
Experiment with the code provided in the tutorials to customize and explore RShiny's features.
Interactive Coding Challenges
Show steps
Solve coding challenges to solidify your grasp of RShiny and its applications.
Show steps
-
Find coding challenges on platforms like HackerRank or Kaggle
-
Implement RShiny solutions to the challenges
Participate in online discussions or forums related to RShiny
Show steps
Engaging with peers can provide different perspectives, clarify concepts, and enhance your understanding of RShiny.
Show steps
-
Join online forums or discussion groups focused on RShiny.
-
Participate in discussions, ask questions, and share your knowledge.
-
Collaborate with others on RShiny projects.
Work through RShiny exercises
Show steps
Complete a series of exercises that will help you practice creating RShiny apps. This will give you hands-on experience and help you to better understand the material covered in the course.
Show steps
-
Follow the RShiny tutorial
-
Complete the exercises in the RShiny documentation
-
Create your own RShiny app
Write a blog post about RShiny
Show steps
Share your knowledge of RShiny with others by writing a blog post. This will help you to solidify your understanding of the material and to reach a wider audience.
Show steps
-
Choose a topic for your blog post
-
Write your blog post
-
Publish your blog post
Build a Simple RShiny Dashboard
Show steps
Create a basic RShiny dashboard to demonstrate your understanding of building interactive web applications.
Show steps
-
Design the layout of your dashboard
-
Create a Shiny app with RStudio
-
Add interactive elements like plots or data tables
Build a simple RShiny app for data visualization
Show steps
Creating your own RShiny app allows you to apply your skills and gain practical experience in designing interactive data visualizations.
Browse courses on
Data Visualization
Show steps
-
Plan the structure and design of your app, including the data you want to visualize and the interactions you want to enable.
-
Write the R code for the app, including the UI and server components.
-
Test and debug the app to ensure it functions correctly.
-
Deploy the app and share it with others.
Build a real-world RShiny application
Show steps
Develop a real-world RShiny app that you can use to solve a problem or improve your workflow. This will give you a chance to apply your skills and knowledge to a practical problem.
Show steps
-
Identify a problem or workflow that you can improve with a RShiny app
-
Design the user interface (UI) for your app
-
Write the server code for your app
-
Deploy your app to a web server
Mentor other RShiny users
Show steps
Help other RShiny users to learn and grow by mentoring them. This will give you a chance to share your knowledge and experience, and to make a positive impact on the community.
Show steps
-
Find opportunities to mentor other RShiny users
-
Provide guidance and support to your mentees
-
Track your progress and make adjustments as needed
Read Advanced R
Show steps
This book provides an in-depth look at the R programming language, covering topics such as data manipulation, statistical modeling, and ggplot2.
View
R Packages
on Amazon
Show steps
Show steps
Show steps
- Read the book
- Work through the exercises in the book
- Apply what you've learned to your own projects
Review JavaScript Basics
Show steps
Refresh your memory on basic JavaScript syntax and concepts to enhance your understanding of the course material.
Browse courses on
JavaScript
Show steps
Show steps
Show steps
- Read through online tutorials or documentation on JavaScript
- Complete coding exercises on platforms like Codecademy or LeetCode
Brush up on introductory programming concepts
Show steps
Reviewing the basics of programming can help strengthen your understanding of RShiny, a key component of this course.
Browse courses on
R Programming
Show steps
Show steps
Show steps
- Read through online tutorials or documentation on R programming fundamentals.
- Complete a few practice exercises or coding challenges to reinforce your understanding.
12 other activities
Expand to see all activities and additional details
Show all 15 activities
Review R basics
Show steps
Review the basics of R, including data structures, functions, and basic statistical analysis. This will help you hit the ground running when you start the course.
Browse courses on
R
Show steps
Show steps
Show steps
- Review the R documentation
- Complete a few R tutorials
- Practice writing your own R code
Meet with other RShiny users
Show steps
Meet with other RShiny users to learn from their experiences and share your own. This will help you to expand your network and stay up-to-date on the latest trends in RShiny development.
Show steps
Show steps
Show steps
- Attend a RShiny meetup or conference
- Join the RShiny community on GitHub
- Connect with other RShiny users on social media
Attend a RShiny workshop
Show steps
Attend a workshop on RShiny to learn from experts and get hands-on experience.
Show steps
Show steps
Show steps
- Find a RShiny workshop in your area
- Register for the workshop
- Attend the workshop
Follow along with RShiny tutorials
Show steps
Engaging with guided tutorials can provide hands-on practice and deepen your understanding of RShiny's capabilities.
Show steps
Show steps
Show steps
- Find online tutorials or courses that cover the fundamentals of RShiny.
- Work through the tutorials, following the instructions and completing the exercises.
- Experiment with the code provided in the tutorials to customize and explore RShiny's features.
Interactive Coding Challenges
Show steps
Solve coding challenges to solidify your grasp of RShiny and its applications.
Show steps
Show steps
Show steps
- Find coding challenges on platforms like HackerRank or Kaggle
- Implement RShiny solutions to the challenges
Participate in online discussions or forums related to RShiny
Show steps
Engaging with peers can provide different perspectives, clarify concepts, and enhance your understanding of RShiny.
Show steps
Show steps
Show steps
- Join online forums or discussion groups focused on RShiny.
- Participate in discussions, ask questions, and share your knowledge.
- Collaborate with others on RShiny projects.
Work through RShiny exercises
Show steps
Complete a series of exercises that will help you practice creating RShiny apps. This will give you hands-on experience and help you to better understand the material covered in the course.
Show steps
Show steps
Show steps
- Follow the RShiny tutorial
- Complete the exercises in the RShiny documentation
- Create your own RShiny app
Write a blog post about RShiny
Show steps
Share your knowledge of RShiny with others by writing a blog post. This will help you to solidify your understanding of the material and to reach a wider audience.
Show steps
Show steps
Show steps
- Choose a topic for your blog post
- Write your blog post
- Publish your blog post
Build a Simple RShiny Dashboard
Show steps
Create a basic RShiny dashboard to demonstrate your understanding of building interactive web applications.
Show steps
Show steps
Show steps
- Design the layout of your dashboard
- Create a Shiny app with RStudio
- Add interactive elements like plots or data tables
Build a simple RShiny app for data visualization
Show steps
Creating your own RShiny app allows you to apply your skills and gain practical experience in designing interactive data visualizations.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Plan the structure and design of your app, including the data you want to visualize and the interactions you want to enable.
- Write the R code for the app, including the UI and server components.
- Test and debug the app to ensure it functions correctly.
- Deploy the app and share it with others.
Build a real-world RShiny application
Show steps
Develop a real-world RShiny app that you can use to solve a problem or improve your workflow. This will give you a chance to apply your skills and knowledge to a practical problem.
Show steps
Show steps
Show steps
- Identify a problem or workflow that you can improve with a RShiny app
- Design the user interface (UI) for your app
- Write the server code for your app
- Deploy your app to a web server
Mentor other RShiny users
Show steps
Help other RShiny users to learn and grow by mentoring them. This will give you a chance to share your knowledge and experience, and to make a positive impact on the community.
Show steps
Show steps
Show steps
- Find opportunities to mentor other RShiny users
- Provide guidance and support to your mentees
- Track your progress and make adjustments as needed
Career center
Learners who complete Creating a Dynamic Web Application using RShiny will develop knowledge and skills
that may be useful to these careers:
Web Developer
Web Developer
A Web Developer designs and develops websites and web applications. This course is an excellent introduction to creating dynamic web applications using RShiny, a valuable skill for Web Developers. Additionally, the course emphasizes user interface (UI) and server interaction, which is a core concept in web development.
Data Analyst
Data Analyst
A Data Analyst transforms raw data into useful information for businesses. This course teaches the skills to explore, clean, and visualize data using R and RShiny, which are foundational skills for data analysis. Additionally, the course emphasizes dynamic web application development, which is a valuable skill for Data Analysts to communicate data analysis results to stakeholders.
Data Scientist
Data Scientist
A Data Scientist uses data to solve business problems. This course helps build a foundation in data analysis and visualization, which are essential skills for Data Scientists. Additionally, the course emphasizes dynamic web application development, which is a valuable skill for Data Scientists to communicate data analysis results to stakeholders.
Business Analyst
Business Analyst
A Business Analyst identifies and analyzes business needs and develops solutions to improve business processes. This course helps build a foundation in data analysis and visualization, which are valuable skills for Business Analysts. Additionally, the course emphasizes dynamic web application development, which is a valuable skill for Business Analysts to communicate analysis results to stakeholders.
Statistician
Statistician
A Statistician collects, analyzes, interprets, and presents data. This course helps build a foundation in data analysis and visualization, which are essential skills for Statisticians. Additionally, the course emphasizes dynamic web application development, which is a valuable skill for Statisticians to communicate analysis results to stakeholders.
Software Engineer
Software Engineer
A Software Engineer designs, develops, and maintains software systems. This course helps build a foundation in software engineering principles, particularly in the context of web application development. RShiny is an open-source R library, so understanding how to use it can be valuable for Software Engineers working with R.
Data Engineer
Data Engineer
A Data Engineer designs, builds, and maintains data systems. This course may be useful for Data Engineers who want to learn how to develop dynamic web applications using RShiny to interact with data systems.
Machine Learning Engineer
Machine Learning Engineer
A Machine Learning Engineer designs, develops, and deploys machine learning models. This course may be useful for Machine Learning Engineers who want to learn how to develop dynamic web applications using RShiny to interact with machine learning models.
Market Researcher
Market Researcher
A Market Researcher analyzes market trends and customer behavior. This course may be useful for Market Researchers who want to learn how to develop dynamic web applications using RShiny to visualize and analyze market data.
Financial Analyst
Financial Analyst
A Financial Analyst analyzes financial data and makes investment recommendations. This course may be useful for Financial Analysts who want to learn how to develop dynamic web applications using RShiny to visualize and analyze financial data.
Product Manager
Product Manager
A Product Manager manages the development and launch of new products. This course may be useful for Product Managers who want to learn how to develop dynamic web applications using RShiny to prototype new products or features.
Quantitative Analyst
Quantitative Analyst
A Quantitative Analyst uses mathematical and statistical models to analyze financial data. This course may be useful for Quantitative Analysts who want to learn how to develop dynamic web applications using RShiny to visualize and analyze financial data.
Actuary
Actuary
An Actuary analyzes and manages financial risk. This course may be useful for Actuaries who want to learn how to develop dynamic web applications using RShiny to visualize and analyze financial data.
UX Designer
UX Designer
A UX Designer designs the user experience of websites and applications. This course may be useful for UX Designers who want to learn how to develop dynamic web applications using RShiny to prototype and test user interfaces.
Epidemiologist
Epidemiologist
An Epidemiologist investigates the causes and spread of diseases. This course may be useful for Epidemiologists who want to learn how to develop dynamic web applications using RShiny to visualize and analyze epidemiological data.
For more career information including salaries, visit:
OpenCourser.com/course/1aezkv/creating
Reading list
We've selected 12 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Creating a Dynamic Web Application using RShiny.
Provides a comprehensive overview of web development with R and Shiny, including topics such as HTML, CSS, JavaScript, and Shiny. It also includes numerous examples and exercises to help you learn how to create your own web applications.
Save
Comprehensive guide to using R Markdown, a powerful tool for creating dynamic, reproducible reports. It covers all the essential concepts, from basic syntax to advanced features. It valuable resource for anyone who wants to learn how to use R Markdown.
Save
Provides a collection of recipes for common data analysis and visualization tasks in R. It valuable resource for both beginners and experienced R users.
Save
Provides a comprehensive overview of R Markdown, a powerful tool for creating dynamic reports, presentations, and web documents. It covers topics such as Markdown syntax, R code embedding, and output customization.
Save
Comprehensive guide to using ggplot2, a powerful R package for creating graphics. It covers all the essential concepts, from basic plots to advanced techniques. It valuable resource for anyone who wants to learn how to use ggplot2 to create beautiful and informative graphics.
Provides a comprehensive overview of modern statistics for biology, including topics such as probability, inference, and modeling. It also includes numerous examples and exercises to help you learn how to apply statistical methods to your own biological data.
Save
Comprehensive guide to using R, a powerful programming language for data analysis. It covers all the essential concepts, from basic syntax to advanced techniques. It valuable resource for anyone who wants to learn how to use R for data analysis.
Provides a comprehensive overview of ggplot2, a powerful R library for creating visualizations. It covers topics such as data aesthetics, plot types, and statistical transformations.
Save
Comprehensive guide to using R for data science. It covers all the essential concepts, from data wrangling to machine learning. It valuable resource for anyone who wants to learn how to use R for data science.
Provides a comprehensive overview of data visualization with R, including topics such as data preparation, plot types, and statistical inference. It also includes numerous examples and exercises to help you learn how to create your own data visualizations.
Provides a comprehensive overview of machine learning with R, including topics such as supervised learning, unsupervised learning, and model evaluation. It also includes numerous examples and exercises to help you learn how to apply machine learning methods to your own data.
Provides a comprehensive overview of deep learning with R, including topics such as neural networks, convolutional neural networks, and recurrent neural networks. It also includes numerous examples and exercises to help you learn how to apply deep learning methods to your own data.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/1aezkv/creating
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Time
1 hours
Via
Coursera
Institution
Coursera Project Network
Instructor
Dr. Nikunj Maheshwari
Good to know
Guides students through the practical stages of uploading, viewing, and extracting data from CSV files
Covers dynamic web-based applications, a high-utility skill in today's tech industry
Helps students understand reactive programming between the user interface (UI) and the server
Involves working with RShiny, a popular open-source R library utilized by data analysts and scientists
Suitable for learners based in North America, with plans for expansion to other regions
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