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María Ignacia España

Este proyecto guiado R para principiantes: Introducción a R y RStudio está diseñado para estudiantes sin conocimientos previos de R. En este curso basado en proyecto de casi 2 horas aprenderás a:

1. Conocer qué es R y para qué se utiliza

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Este proyecto guiado R para principiantes: Introducción a R y RStudio está diseñado para estudiantes sin conocimientos previos de R. En este curso basado en proyecto de casi 2 horas aprenderás a:

1. Conocer qué es R y para qué se utiliza

2. Utilizar RStudio, conocer sus principales beneficios

3. Utilizar comandos básicos de R para análisis de datos

Para lograr esto trabajaremos las siguientes tareas:

1. Conociendo R

2. Conociendo RStudio

3. Utilizando operadores aritméticos y comparativos en R

4. Utilizando contenedores de datos en R

5. Conociendo los ciclos en R

Este es un curso único ya que podrás aprender de manera práctica y simple cómo trabajar con regresiones en R, es por esto que está recomendado para ti si no tienes conocimientos previos en R pero si ganas de aprendera trabajar con esta herramienta, mediante RStudio y comandos básicos que luego podrás utilizar en análisis de datos.

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What's inside

Syllabus

Module 1

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Curso introductorio que desarrolla habilidades para análisis de datos de manera práctica y accesible
Enseña el uso de RStudio, una herramienta esencial para el análisis de datos en R
Dirigido a principiantes sin experiencia previa en R, permitiendo un aprendizaje gradual
Incluye ejercicios prácticos que facilitan la comprensión y aplicación de los conceptos
Abarca temas fundamentales de R, como operadores, contenedores de datos y ciclos

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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 R para principiantes: Introducción a R y RStudio with these activities:
Revise basic arithmetic and algebra
Solid arithmetic and algebra skills will help with understanding statistical concepts.
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  • Review basic operations such as addition, subtraction, multiplication, and division.
  • Practice solving simple equations.
Watch video tutorials on R basics
Watching video tutorials will help you grasp the fundamentals of R and RStudio.
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  • Find video tutorials on YouTube or other online platforms.
  • Watch tutorials on topics such as data types, operators, and control flow.
Solve coding exercises on R exercises
Solving coding exercises will help you apply your understanding of R and improve your problem-solving skills.
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  • Find coding exercises on websites like HackerRank or LeetCode.
  • Solve exercises on topics such as data manipulation, visualization, and statistical analysis.
Five other activities
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Create a cheat sheet of R commands
Creating a cheat sheet will help you memorize and quickly reference important R commands.
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  • List down frequently used R commands.
  • Organize commands by topic or function.
Build a small data analysis project
Building a data analysis project will help you apply your skills and showcase your understanding of R.
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  • Choose a dataset and research a topic.
  • Clean and explore the data.
  • Perform statistical analysis and visualize the results.
Join a study group or online forum
Participating in a study group or online forum will allow you to connect with peers, ask questions, and learn from others.
Browse courses on R
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  • Find a study group or online forum dedicated to R or data analysis.
  • Participate in discussions and ask questions.
Help other students in R or data analysis
Mentoring others will reinforce your understanding of R and help you develop your communication skills.
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  • Offer to help classmates or join a mentoring program.
  • Provide guidance on R concepts, coding exercises, or data analysis projects.
Contribute to open-source R projects
Contributing to open-source projects will expose you to real-world code and best practices.
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  • Find open-source R projects on GitHub or other platforms.
  • Contribute by fixing bugs, adding features, or improving documentation.

Career center

Learners who complete R para principiantes: Introducción a R y RStudio will develop knowledge and skills that may be useful to these careers:
Data Scientist
Data Scientists use various techniques to extract knowledge and insights from data. This course is a good starting point for those interested in a career as a Data Scientist, as it provides a foundation in R and RStudio, which are widely used in the field.
Data Visualization Specialist
Data Visualization Specialists create visual representations of data to communicate insights. This course can help build a foundation for a career as a Data Visualization Specialist, as it provides a foundation in data analysis and visualization.
Data Analyst
Data Analysts translate raw data into information that businesses can use to make better decisions. A background in R and RStudio is common because it is a platform that allows for the analysis, cleaning, and representation of data. Taking this course R para principiantes: Introducción a R y RStudio will help build a foundation for success in this role.
Machine Learning Engineer
Machine Learning Engineers apply machine learning algorithms to solve problems. This course can help build a foundation for a career as a Machine Learning Engineer, as it provides a foundation in R, which is a popular language for machine learning.
Biostatistician
Biostatisticians apply statistical methods to solve problems in the health sciences. This course can help build a foundation for a career as a Biostatistician, as it provides a foundation in data analysis and interpretation.
Business Analyst
Business Analysts bridge the gap between business and IT by analyzing data to identify inefficiencies and create solutions. The course's focus on using R for data analysis and visualization can be helpful for those interested in a career as a Business Analyst.
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze financial data. This course can help build a foundation for a career as a Quantitative Analyst, as it provides a foundation in R, which is used in some quantitative analysis applications.
Epidemiologist
Epidemiologists investigate the causes and distribution of diseases and injuries in populations. This course can help build a foundation for a career in Epidemiology, as it provides a foundation in data analysis and interpretation.
Market Researcher
Market Researchers analyze market trends, customer behaviors, and industry data to help businesses make informed decisions. This course can help build a foundation for a career in Market Research because of its focus on data analysis and interpretation.
Risk Analyst
Risk Analysts identify, assess, and mitigate risks. This course can help build a foundation for a career as a Risk Analyst, as it provides a foundation in data analysis and interpretation.
Actuary
Actuaries use mathematical and statistical techniques to assess risk and uncertainty. The course's focus on using R for data analysis and interpretation can be helpful for those interested in a career as an Actuary, as it is a common tool in the field.
Statistician
Statisticians collect, interpret, and present data. They also develop and apply statistical methods, theories, and techniques to solve problems in various fields. Because of the course's focus on using R for data analysis, it may be useful for those interested in a career as a Statistician.
Data Engineer
Data Engineers build, maintain, and manage data systems. This course may be useful for those interested in a career as a Data Engineer, as it provides a foundation in R.
Financial Analyst
Financial Analysts make recommendations on investments, analyze market trends, and forecast financial performance. This course may be useful for those interested in a career as a Financial Analyst, as it provides a foundation in data analysis and interpretation.
Software Engineer
Software Engineers design, develop, and maintain software systems. This course may be useful for those interested in a career as a Software Engineer, as it provides a foundation in R, which is used in some software development applications.

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 R para principiantes: Introducción a R y RStudio.
Este libro es la documentación oficial del lenguaje y el entorno R. Proporciona una referencia completa de la sintaxis y las funciones de R. Es un recurso valioso para aquellos que buscan una comprensión profunda del lenguaje R.
Este libro enseña los fundamentos de la ciencia de datos utilizando R. Cubre temas como la recopilación, la limpieza y el análisis de datos, así como la visualización y la comunicación de los resultados. Es un recurso valioso para aquellos que desean utilizar R para proyectos de ciencia de datos.
Este libro integral cubre una amplia gama de temas en R, desde el análisis de datos hasta los gráficos y la programación. Es un recurso valioso para usuarios intermedios y avanzados que buscan profundizar sus conocimientos de R.
Este libro es un texto integral sobre el aprendizaje estadístico utilizando R. Cubre temas como la regresión, la clasificación y el clustering. Es un recurso valioso para aquellos que buscan profundizar en los métodos de aprendizaje automático.
Este libro proporciona una exploración avanzada de las capacidades de R. Cubre temas como la programación funcional, el manejo de datos avanzados y la creación de paquetes. Es un recurso valioso para aquellos que buscan ampliar sus conocimientos de R.
Este libro proporciona una guía completa de RStudio, cubriendo temas como la edición de código, la gestión de proyectos y el uso de paquetes. Es particularmente útil para aquellos que desean utilizar RStudio para el análisis y la visualización de datos.
Este libro enseña los fundamentos del aprendizaje profundo utilizando R. Cubre temas como redes neuronales, redes convolucionales y redes recurrentes. Es un recurso valioso para aquellos que desean utilizar R para proyectos de aprendizaje profundo.
Este libro proporciona una guía práctica para el uso de R en el mundo real. Cubre temas como el análisis de datos, la visualización y el desarrollo de aplicaciones. Es un recurso valioso para aquellos que buscan aprender a utilizar R de manera efectiva para resolver problemas del mundo real.
Este libro ofrece una introducción completa a la programación en R para la ciencia de datos. Cubre temas como el manejo, el análisis y la visualización de datos. Es un recurso valioso para aquellos que buscan desarrollar habilidades prácticas en el uso de R para proyectos de ciencia de datos.
Este libro proporciona recetas para crear gráficos personalizados y sofisticados utilizando R. Cubre temas como la creación de gráficos estáticos y animados, la personalización de gráficos y la integración de gráficos en informes. Es un recurso valioso para aquellos que buscan mejorar sus habilidades de visualización de datos.
Este libro ofrece una introducción accesible al análisis estadístico utilizando R. Cubre temas como pruebas de hipótesis, regresión y análisis multivariante. Es un recurso útil para aquellos que buscan comprender los conceptos básicos del análisis estadístico.

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