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María Ignacia España
En este curso basado en un proyecto y de 1 hora de duración, aprenderás a crear aplicaciones interactivas con R shiny. Es un proyecto intermedio, por lo cual es importante tener alguna noción de R, sin embargo se explica desde el inicio como desarrollar las...
Read more
En este curso basado en un proyecto y de 1 hora de duración, aprenderás a crear aplicaciones interactivas con R shiny. Es un proyecto intermedio, por lo cual es importante tener alguna noción de R, sin embargo se explica desde el inicio como desarrollar las...
Read more
En este curso basado en un proyecto y de 1 hora de duración, aprenderás a crear aplicaciones interactivas con R shiny. Es un proyecto intermedio, por lo cual es importante tener alguna noción de R, sin embargo se explica desde el inicio como desarrollar las aplicaciones. Se trabajará primer comprendiendo la estructura de las aplicaciones, observando ejemplos pre diseñados, para luego crear una aplicación desde 0 con distintos widgets interactivos. También aprenderemos a subir archivos y utilizarlos en la aplicación.
A lo largo del proyecto realizaremos distintos ejemplos, los cuales puedes seguir en tiempo real, además de repetirlos hasta que lo comprendas a cabalidad.
Register for this course and see more details by visiting:
OpenCourser.com/course/9nzkv9/crea
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Enriches learners with skills, knowledge, and tools that are highly relevant in an academic setting
Strengthens an existing foundation for intermediate learners
Builds a strong foundation for beginners
Develops professional skills or deep expertise in a particular topic or set of topics
Offers hands-on labs and interactive materials
Takes a creative approach to an otherwise established topic, field, or subject
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Reviews summary
Basic intro to r shiny
This beginner-intermediate course teaches students who already know a little R the basics of R Shiny and how to create interactive applications. After learning how applications are structured, students follow along in real time and create an application with interactive widgets from scratch. They also learn how to upload files and use them in the application.
Lessons feature plenty of real-time examples.
"A lo largo del proyecto realizaremos distintos ejemplos, los cuales puedes seguir en tiempo real..."
The dictation system may cause issues with using the dashboard.
"el sistema de dictado no me permitió hacer uso del Dashboard en ningún momento del curso (no conectó nunca)"
No source files or exercises are provided.
"No data and no source files provided."
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 Crea tus dashboards y aplicaciones interactivas con R Shiny with these
activities:
Review Basic Statistics
Show steps
Help prepare to understand statistical methods used in the course.
Browse courses on
Statistics
Show steps
-
Review basic concepts such as mean, median, and standard deviation.
-
Practice calculating these statistics using online resources or a textbook.
Organize Course Materials
Show steps
Enhance accessibility and improve understanding by organizing course materials.
Show steps
-
Create a central repository for all lecture notes, assignments, and resources.
-
Develop a system for naming and organizing files consistently.
-
Periodically review and整理材料 to identify any gaps or areas that need more attention.
Explore Hands-on Tutorials
Show steps
Complement course content with practical examples and hands-on exercises.
Browse courses on
R Programming
Show steps
-
Identify online tutorials or documentation that align with course topics.
-
Follow along with the tutorials, implementing code and experimenting with different approaches.
-
Create small projects or exercises to apply the concepts learned in the tutorials.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Practice Coding Challenges
Show steps
Reinforce coding concepts and improve problem-solving skills.
Show steps
-
Join an online coding challenge platform.
-
Start with simple challenges and gradually increase the difficulty.
-
Spend time analyzing and understanding the solutions to improve your approach.
Participate in Study Groups
Show steps
Engage in discussions, share insights, and learn from peers.
Show steps
-
Find or create a study group with classmates who share similar learning goals.
-
Meet regularly to discuss course material, solve problems, and quiz each other.
-
Take turns leading the discussions to foster active participation and diverse perspectives.
Create a Course Summary
Show steps
Enhance understanding and solidify key concepts through active recall.
Show steps
-
After each lecture or module, summarize the main points in your own words.
-
Organize the summaries into a cohesive document or presentation.
-
Review and refine the summary regularly to improve retention.
Develop a Shiny Application
Show steps
Apply course concepts by building a functional interactive application.
Show steps
-
Design the application's layout and user interface.
-
Implement the necessary R code and widgets for functionality.
-
Test and refine the application to ensure it meets the desired outcomes.
Review Basic Statistics
Show steps
Help prepare to understand statistical methods used in the course.
Browse courses on
Statistics
Show steps
Show steps
Show steps
- Review basic concepts such as mean, median, and standard deviation.
- Practice calculating these statistics using online resources or a textbook.
Organize Course Materials
Show steps
Enhance accessibility and improve understanding by organizing course materials.
Show steps
Show steps
Show steps
- Create a central repository for all lecture notes, assignments, and resources.
- Develop a system for naming and organizing files consistently.
- Periodically review and整理材料 to identify any gaps or areas that need more attention.
Explore Hands-on Tutorials
Show steps
Complement course content with practical examples and hands-on exercises.
Browse courses on
R Programming
Show steps
Show steps
Show steps
- Identify online tutorials or documentation that align with course topics.
- Follow along with the tutorials, implementing code and experimenting with different approaches.
- Create small projects or exercises to apply the concepts learned in the tutorials.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Practice Coding Challenges
Show steps
Reinforce coding concepts and improve problem-solving skills.
Show steps
Show steps
Show steps
- Join an online coding challenge platform.
- Start with simple challenges and gradually increase the difficulty.
- Spend time analyzing and understanding the solutions to improve your approach.
Participate in Study Groups
Show steps
Engage in discussions, share insights, and learn from peers.
Show steps
Show steps
Show steps
- Find or create a study group with classmates who share similar learning goals.
- Meet regularly to discuss course material, solve problems, and quiz each other.
- Take turns leading the discussions to foster active participation and diverse perspectives.
Create a Course Summary
Show steps
Enhance understanding and solidify key concepts through active recall.
Show steps
Show steps
Show steps
- After each lecture or module, summarize the main points in your own words.
- Organize the summaries into a cohesive document or presentation.
- Review and refine the summary regularly to improve retention.
Develop a Shiny Application
Show steps
Apply course concepts by building a functional interactive application.
Show steps
Show steps
Show steps
- Design the application's layout and user interface.
- Implement the necessary R code and widgets for functionality.
- Test and refine the application to ensure it meets the desired outcomes.
Career center
Learners who complete Crea tus dashboards y aplicaciones interactivas con R Shiny will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
Data Scientists use data to solve complex problems. They develop and implement machine learning models to identify patterns and predict outcomes. This course can help you develop the skills you need to become a Data Scientist, including data visualization, statistical analysis, and machine learning.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers develop and implement machine learning models to solve complex problems. They work with data to create innovative solutions to real-world problems. This course can help you develop the skills you need to become a Machine Learning Engineer, including data visualization, statistical analysis, and machine learning.
Business Analyst
Business Analyst
Business Analysts use data to help businesses improve their performance. They identify problems, develop solutions, and communicate results to stakeholders. This course can help you develop the skills you need to become a Business Analyst, including data visualization, statistical analysis, and machine learning.
Statistician
Statistician
Statisticians use data to make informed decisions. They design and conduct experiments, analyze data, and interpret results. This course can help you develop the skills you need to become a Statistician, including data visualization, statistical analysis, and machine learning.
Data Architect
Data Architect
Data Architects design and implement data management solutions. They work with data to ensure that it is organized, accessible, and secure. This course can help you develop the skills you need to become a Data Architect, including data visualization, statistical analysis, and machine learning.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. They work with data to create innovative solutions to real-world problems. This course can help you develop the skills you need to become a Software Engineer, including data visualization, statistical analysis, and machine learning.
Data Analyst
Data Analyst
Data Analysts use data to help businesses make better decisions. They collect, clean, and analyze data to identify trends and patterns. This course can help you develop the skills you need to become a Data Analyst, including data visualization, statistical analysis, and machine learning.
Database Administrator
Database Administrator
Database Administrators maintain and manage databases. They work with data to ensure that it is secure, reliable, and accessible. This course can help you develop the skills you need to become a Database Administrator, including data visualization, statistical analysis, and machine learning.
Web Developer
Web Developer
Web Developers design, develop, and maintain websites. They work with data to create interactive and engaging experiences for users. This course can help you develop the skills you need to become a Web Developer, including data visualization, statistical analysis, and machine learning.
Information Security Analyst
Information Security Analyst
Information Security Analysts protect computer systems and networks from unauthorized access or damage. They work with data to identify and mitigate security risks. This course can help you develop the skills you need to become an Information Security Analyst, including data visualization, statistical analysis, and machine learning.
Financial Analyst
Financial Analyst
Financial Analysts use data to evaluate investments and make recommendations to clients. They analyze financial data, develop models, and present their findings to clients. This course can help you develop the skills you need to become a Financial Analyst, including data visualization, statistical analysis, and machine learning.
Marketing Analyst
Marketing Analyst
Marketing Analysts use data to understand customer behavior and develop marketing campaigns. They analyze market data, develop models, and present their findings to clients. This course can help you develop the skills you need to become a Marketing Analyst, including data visualization, statistical analysis, and machine learning.
Risk Analyst
Risk Analyst
Risk Analysts identify and assess risks to organizations. They work with data to develop and implement risk management strategies. This course can help you develop the skills you need to become a Risk Analyst, including data visualization, statistical analysis, and machine learning.
Data Engineer
Data Engineer
Data Engineers build and maintain data pipelines that collect, clean, and process data. They work with data to ensure that it is accurate, reliable, and accessible. This course can help you develop the skills you need to become a Data Engineer, including data visualization, statistical analysis, and machine learning.
Security Analyst
Security Analyst
Security Analysts investigate and respond to security breaches. They work with data to identify and mitigate security risks. This course can help you develop the skills you need to become a Security Analyst, including data visualization, statistical analysis, and machine learning.
For more career information including salaries, visit:
OpenCourser.com/course/9nzkv9/crea
Reading list
We've selected seven 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
Crea tus dashboards y aplicaciones interactivas con R Shiny.
Save
Provides a comprehensive guide to using R Markdown, a powerful tool for creating dynamic, reproducible reports and documents. It valuable resource for those looking to use R Markdown for technical writing, data analysis, and more.
Save
Provides a comprehensive introduction to R, covering topics such as data structures, data manipulation, and statistical analysis. It valuable resource for those new to R, as well as those looking to expand their knowledge.
Save
Provides a comprehensive introduction to data science using R, covering topics such as data wrangling, data analysis, and machine learning. It valuable resource for those new to data science, as well as those looking to expand their knowledge.
Save
Provides a comprehensive guide to advanced topics in R, covering topics such as object-oriented programming, functional programming, and high-performance computing. It valuable resource for those looking to expand their knowledge of R.
Provides a comprehensive guide to using ggplot2, a powerful R package for creating visually appealing and informative data visualizations. It valuable resource for those looking to create beautiful and effective data visualizations.
Provides a comprehensive guide to the art of R programming, covering topics such as code style, data structures, and algorithm design. It valuable resource for those looking to improve their R programming skills.
Provides a comprehensive introduction to R, covering topics such as data manipulation, statistical analysis, and machine learning. It valuable resource for those new to R, as well as those looking to expand their knowledge.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/9nzkv9/crea
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Time
3 hours
Via
Coursera
Institution
Coursera Project Network
Instructor
María Ignacia España
Good to know
Enriches learners with skills, knowledge, and tools that are highly relevant in an academic setting
Strengthens an existing foundation for intermediate learners
Builds a strong foundation for beginners
Develops professional skills or deep expertise in a particular topic or set of topics
Offers hands-on labs and interactive materials
Takes a creative approach to an otherwise established topic, field, or subject
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