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Updated in [March 06th, 2023]
This course, Become a R Shiny Ninja, is designed to help participants learn how to create a Shiny app. Participants will learn about advanced visualisation software that can bring their charts and maps to life. They will also learn how to personalise the app using HTML and CSS formatting, as well as how to use functions to make their app run faster. Additionally, participants will learn about design elements placement for the app, how to include various elements such as checkbox, dropdowns, datinputs, output elements such as HTML text, datatables, charts, maps, dependent elements, export and import functionalities, TabPanel and condition Panel, notification menus and task menus, and how to change body, header and sidebar color, icons using HTML tags.
[Applications]
After completing this course, participants will be able to apply their knowledge to create a R Shiny app. They will be able to use advanced visualisation software to bring their charts and maps to life. They will be able to personalise the app using HTML and CSS formatting, and use functions to make the app run faster. Participants will also be able to design elements placement for the app, include various elements such as checkbox, dropdowns, datinputs, and output elements such as HTML text, datatables, charts, maps. They will also be able to include dependent elements, export and import functionalities, use TabPanel and condition Panel, notification menus and task menus, and change body, header and sidebar color, icons using HTML tags.
[Career Paths]
1. R Shiny Developer: R Shiny Developers create web applications and dashboards using R Shiny. They are responsible for designing and developing the user interface, coding the application, and testing the application. They must be knowledgeable in HTML, CSS, and JavaScript, as well as R Shiny. They must also be able to troubleshoot any issues that arise.
2. R Shiny Data Analyst: R Shiny Data Analysts use R Shiny to create visualizations and analyze data. They must be knowledgeable in data analysis techniques, such as regression analysis, clustering, and time series analysis. They must also be able to interpret the results of their analysis and present them in a meaningful way.
3. R Shiny Consultant: R Shiny Consultants provide advice and guidance to clients on how to use R Shiny to create web applications and dashboards. They must be knowledgeable in R Shiny and have experience in developing applications. They must also be able to provide advice on how to optimize the application for the best user experience.
4. R Shiny Designer: R Shiny Designers create the look and feel of the application. They must be knowledgeable in HTML, CSS, and JavaScript, as well as R Shiny. They must also be able to create custom designs that are visually appealing and user-friendly. They must also be able to troubleshoot any issues that arise.
[Education Paths]
1. Bachelor of Science in Computer Science: This degree path focuses on the fundamentals of computer science, including programming, software engineering, and computer architecture. It also covers topics such as artificial intelligence, machine learning, and data science. With the increasing demand for data-driven solutions, this degree path is becoming increasingly popular.
2. Master of Science in Data Science: This degree path focuses on the application of data science techniques to solve real-world problems. It covers topics such as data mining, machine learning, and predictive analytics. It also covers topics such as natural language processing, computer vision, and deep learning. This degree path is becoming increasingly popular as businesses are looking for ways to leverage data to gain insights and make better decisions.
3. Master of Science in Artificial Intelligence: This degree path focuses on the development of intelligent systems and their applications. It covers topics such as machine learning, natural language processing, computer vision, and robotics. It also covers topics such as game theory, decision theory, and optimization. This degree path is becoming increasingly popular as businesses are looking for ways to leverage AI to automate processes and gain insights.
4. Doctor of Philosophy in Computer Science: This degree path focuses on advanced topics in computer science, such as artificial intelligence, machine learning, and data science. It also covers topics such as computer architecture, software engineering, and distributed systems. This degree path is becoming increasingly popular as businesses are looking for ways to leverage advanced technologies to gain insights and make better decisions.
Course Syllabus
How to setup a simple web frontend in RShiny?
How to add multiple input functions and structure them?
How to customize app for more user control?
How to create different views of same app?
