Full Stack Development for Data Applications with R (Pre-registration)
IMPORTANT INFORMATION: Pre-registration for this course is now available. Following your completion of the questionnaire linked below, you will be contacted by Digital Learning Hub to approve your registration.
Submit a pre-registration request
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 and full stack development with R. The six modules of this track will review R foundations and Version Control with GitHub, then cover front end and back end development, automation of data pipelines and deployment processes, and creating business value with enterprise applications.
This is an intermediate to advanced level course. What I need to know, 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 learning track structured?
Using a modular structure, six separate courses can stand alone, or combine to allow flexible options to fit your needs:
- Full Learning Track: enroll in the entire series of modules to gain a comprehensive understanding of advanced R programming, covering both front-end and back-end development, as well as practical applications in business and data science. (36 days, or 252 hours)
- Individual Modules: choose to enroll in specific modules that match your interests or professional objectives. Each module is standalone and designed to provide in-depth knowledge on the specified topic.
- Micro-track one: enroll in modules 1,2, 3 & 6 to focus on front end. (21 days, or 147 hours)
- Micro--track two: enroll in modules 1, 4,5 & 6 for focus on back end. (21 days, or 147 hours)
- Core modules: Modules one and six are common to all tracks, and are recommended to all participants wishing to gain a comprehensive overview of application development with R.
Content
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.
Content:
○ Introduction to RStudio and R essentials
○ Using GitHub for version control and collaboration
○ Creating and managing repositories
○ Integrating GitHub with Rstudio
○ Version control and conflict resolution
○ Automating workflows with GitHub Actions.
Goal: The student will learn how to effectively adopt GitHub in the context of R programming and understand the benefits of using version control.
Module 2: Front End with R Shiny. Learn to create interactive web applications using the R Shiny package.
Content:
○ Basic structure of a Shiny application
○ Reactive inputs and outputs
○ Customizing user interfaces
○ Practical examples of interactive dashboards
Goal: The student will be able to build and customize interactive web applications using R Shiny.
Module 3: Advanced R Shiny. This advanced course builds on the basics of R Shiny to develop more complex web applications.
Content:
○ User session management
○ Database integration
○ Advanced use of Shiny modules
○ Deploying Shiny applications on servers
Goal: The student will develop the skills to create and deploy sophisticated R Shiny applications integrated with databases.
Module 4: Back End Development with R. Focus on backend development, including databases and APIs.
Content:
○ Database integration with R
○ Creating APIs using the plumber package
○ Securing APIs
○ Best practices for API development
Goal: The student will learn to develop secure and efficient backend systems using R.
Module 5: Continuous Integration and Continuous Deployment (CI/CD). This module covers the automation of data pipelines and deployment processes.
Content:
○ Using Rscript to automate R tasks
○ Setting up CI/CD pipelines with Jenkins
○ Managing package dependencies with packrat or renv
○ Practical cases of data flow automation
Prerequisites: Basic knowledge of R scripting
Goal: The student will be able to set up and manage CI/CD pipelines to automate and streamline R programming workflows.
Module 6: Business Applications of R. Applying R to create business value through various enterprise applications.
Content:
○ Case studies on workplace applications
○ Developing business solutions with R
○ Creating dashboards and reports
Goal: The student will understand how to apply R to solve real-world business problems and create value in an enterprise setting.
Learning Outcomes
- 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.
Additional Information
IMPORTANT INFORMATION: REGISTRATION IS NOT YET OPEN FOR THIS COURSE. MORE INFORMATION COMING SOON. PLEASE NOTE Registration for this course will be subject to validation by the Digital Learning Hub. When you register for a module, your application will need to be validated. Therefor, it is important that you choose the payment option “bank transfer”, but you must NOT MAKE ANY PAYMENT OR BANK TRANSFER until your application is approved. See the pre-requisites above for more details.Organised By
Digital Learning Hub Luxembourg
Certification
Participation OnlyPrerequisites
Enrollment is subject to validation on the following criteria:
- Level: this learning track begins at intermediate level. Participants must have basic programming skills and knowledge of R.
- Availability: applicants are asked to commit to attend all the training hours of the module(s) for which they register
- Motivation: applicants are asked to demonstrate the relevance of the course for their jobs, career plan, or project
For an introduction to R Programming, we recommend the following DLH course taking place on 5, 6 & 7 February 2025:
Introduction to R Programming Language - Digital Learning Hub
For registrations in separate individual modules, please see the course page of each module and the prerequisites of each module.
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Courses
This course is a learning track, it includes all of the following trainings.