Full Stack Development for Data Applications with R

R is widely recognized as a programming language for data science, statistics, and visualization. Thanks to its growing ecosystem of tools and frameworks, it can also be used for full-stack development. The course will teach advanced web development, database integration, automation, and business application development. Participants will gain hands-on experience in building interactive dashboards with R Shiny, integrating databases, setting up APIs, and automating workflows.

When would you want to do this, and what are the advantages of using R for full stack development?

• You want do rapid prototyping to quickly create and test interactive apps with R-Shiny.
• You are developing data-driven apps, and you want seamless integration of statistical models and machine learning in your stack.
• You want end-to-end analytics with complete data processing, analysis, and visualization in a single stack.

Who is this course for?

• Your focus is on on data analytics, visualization, or reporting.
• Your data team is using R and wants to refine its processes or expand its capabilities, whether improving efficiency or exploring full-stack development.
• You are a developer seeking to build and deploy full-stack applications using R.
• You are a students familiar with R in an academic setting who wants to understand how R can be applied in real business scenarios and full-stack projects.
• You are a tech enthusiasts with some initial R knowledge looking to specialise further.

What will you learn in this course?

This learning track is designed to provide comprehensive training in advanced R programming, catering to both professionals looking to enhance their skills and persons seeking to apply R in specific contexts. Participants have the flexibility to enroll in the complete learning track or select individual modules based on their needs and prior knowledge.

This is an intermediate to advanced level course. What prerequisites do I need in order to be able to take part in this course?

Applicants should have foundational knowledge of the R language and at least foundational skills in programming (not necessarily R, but an understanding of programming concepts and some experience is required). Please see each module's pre-requisites for a good understanding of the content and level.

How is the content structured across the six modules?

Below are the content summaries of each module. Consult the course sheets for each module for their detailed descriptions.

Module 1: R Basics and Version Control with GitHub. This module focuses on essential tools and best practices for R programming, with a special emphasis on version control using GitHub. 

Module 2: Front End with R Shiny.  Learn to create interactive web applications using the R Shiny package. 

Module 3: Advanced R Shiny. This advanced course builds on the basics of R Shiny to develop more complex web applications. 

Module 4: Back End Development with R. Focus on backend development, including databases and APIs. 

Module 5: Continuous Integration and Deployment (CI/CD). This module covers the automation of data pipelines and deployment processes. 

Module 6: End-to-End Data Applications. Applying R to create business value through various enterprise applications. This module is a five-day capstone project focused entirely on practice. Students will combine all the technologies and concepts learned in Modules 1 to 5.

• Develop advanced R Shiny applications with dynamic user interfaces.
• Integrate databases and create secure APIs for back-end systems using R.
• Set up continuous integration and deployment (CI/CD) pipelines for data automation.
• Apply R programming to solve business problems and create data-driven applications.