Ciencia de Datos: Fundamentos de R from edX

En este curso, les presentaremos los fundamentos de la programación en R. Creemos que se retiene mejor el conocimiento de R cuando se aplica a problemas específicos y por eso utilizaremos un set de datos del mundo real relacionado al crimen en Estados Unidos. Adquirirán las habilidades necesarias en R para abordar preguntas fundamentales sobre las disparidades en asesinatos entre los diferentes estados.

Primero, estudiaremos las funciones y los tipos de datos en R. Luego, explicaremos cómo trabajar con vectores y cuándo utilizar funciones avanzadas.. Además, aprenderemos a aplicar conceptos generales de programación, como los comandos condicionales "if-else" y los bucles-for. Terminaremos estudiando el wrangling, análisis y visualización de datos.

En este curso, nos enfocamos en construir una base sólida en vez de abordar todas las técnicas de R. La demanda de profesionales cualificados en ciencia de datos está creciendo rápidamente, y este curso ofrece conceptos que servirán de bases para aprender destrezas que los ayudarán a enfrentar los desafíos del análisis de datos del mundo real.

What's inside

Learning objectives

La sintaxis esencial para r
Los conceptos de programación fundamentales en r como tipos de datos, vectores, aritmética e indexación

Cómo realizar operaciones en r incluyendo clasificación, discusión de datos utilizando dplyr y a crear gráficos
Usted aprenderá:

La sintaxis esencial para r
Los conceptos de programación fundamentales en r como tipos de datos, vectores, aritmética e indexación
Cómo realizar operaciones en r incluyendo clasificación, discusión de datos utilizando dplyr y a crear gráficos
Usted aprenderá:

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Perfecto para principiantes que buscan una base sólida en los conceptos esenciales de R

Enseña las habilidades básicas para abordar problemas relacionados con las disparidades de asesinatos

Tiene como objetivo desarrollar habilidades para abordar desafíos de análisis de datos del mundo real

El uso de un conjunto de datos del mundo real proporciona relevancia práctica

Se enfoca en construir una base sólida en lugar de cubrir temas exhaustivamente, lo que permite un aprendizaje más profundo

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 Ciencia de Datos: Fundamentos de R with these activities:

Review the basics of programming

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This activity will prepare you for the course by helping you remember the foundational knowledge of R programming, which will increase learning outcomes.

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Review the R syntax and data types.
Practice working with vectors and matrices.
Brush up on conditional statements and loops.

Organize a study group with classmates

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Regularly meeting with classmates to discuss course material in a group setting will enhance your understanding through collaborative learning.

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Find a few classmates who are interested in forming a study group.
Decide when and where to meet.
Establish a schedule and create a list of topics to cover each session.

Complete the R tutorials on Coursera

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These tutorials will provide hands-on practice with R programming, which will reinforce the concepts you learn in the course.

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Sign up for the Coursera R tutorials.
Complete the introductory module.
Practice the exercises in each module.

Seven other activities

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Seek guidance from an experienced R programmer

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Connecting with a mentor will have a positive impact on your course work and provide valuable insights from someone with experience in the field.

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Identify potential mentors who are experienced R programmers.
Reach out to your potential mentors and ask for their guidance.
Establish regular communication with your mentor.

Working with Vectors in R

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Complete a series of exercises to practice creating, manipulating, and summarizing vectors in R.

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Create vectors of different data types (e.g., numeric, character, logical).
Perform operations on vectors (e.g., addition, subtraction, multiplication).
Extract and subset elements from vectors using indexing.

Data Wrangling with dplyr

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Follow a guided tutorial on using the dplyr package to filter, transform, and summarize data in R.

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Install and load the dplyr package.
Learn the basics of data wrangling with dplyr (e.g., filtering, selecting, grouping).
Apply dplyr functions to real-world datasets.

Solve R coding challenges on HackerRank

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Solving R coding challenges will strengthen your programming skills and improve your problem-solving abilities.

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Create an account on HackerRank.
Select the R programming track.
Solve the coding challenges in the track.

Data Visualization Project

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Create a data visualization project that showcases your understanding of data analysis and visualization techniques in R.

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Choose a dataset and research a topic of interest.
Clean and prepare the data for visualization.
Create visualizations using appropriate R packages (e.g., ggplot2).
Interpret and communicate the results of the visualization.

Build a data visualization project in R

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This project will allow you to apply the R programming skills you learn in the course to a real-world problem, which will deepen your understanding of the material.

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Choose a dataset to analyze.
Clean and prepare the data.
Create a data visualization using R.

Participate in an R programming competition

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Participating will provide you with a practical and simulated environment to test your knowledge and refine your R programming capabilities.

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Register for the competition.
Find an R programming competition that aligns with your interests.
Develop a strategy for solving the competition's challenges.

Career center

Learners who complete Ciencia de Datos: Fundamentos de R will develop knowledge and skills that may be useful to these careers:

Data Analyst

A Data Analyst is someone who collects, processes, and analyzes data to help businesses make informed decisions. This course is a great introduction to data analysis, and it will teach you the skills you need to succeed in this role. With its focus on real-world data and challenges, you will learn how to apply the concepts taught in this course to solve problems in industry.

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Data Scientist

Data Scientists use their knowledge in math, statistics, and computer science to solve business problems. This course will teach you the skills needed to succeed in this field. By providing students with a solid base on which to advance their skillset, this course will serve as a cornerstone of your path toward becoming a well-rounded Data Scientist.

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Machine Learning Engineer

Machine Learning Engineers build and deploy machine learning models to solve business problems. This course will provide the necessary building blocks to excel in this role. You will learn the fundamentals of R, which is a popular programming language for machine learning.

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Business Analyst

Business Analysts use data and technology to solve business problems. This course will give you foundational skills to help you succeed in this role. With a solid understanding of R and its uses, you will be well-equipped to assist Business Analysts with data analysis.

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Statistician

Statisticians use data to solve problems. This course may be useful for those looking to enter this field. By familiarizing yourself with R, you will have an advantage in learning statistical methods and their applications.

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Financial Analyst

Financial Analysts use data to make investment decisions. This course may be useful for those looking to enter this field. You will learn how to use R to analyze financial data and build models.

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Quantitative Analyst

Quantitative Analysts use data to make investment decisions. This course may be useful for those looking to enter this field. You will learn how to use R to analyze financial data and build models.

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Market Researcher

Market Researchers use data to understand consumer behavior. This course may be useful for those looking to enter this field. You will learn how to use R to analyze data and identify trends.

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Actuary

Actuaries use data to assess risk. This course may be useful for those looking to enter this field. You will learn how to use R to analyze data and build models.

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Data Engineer

Data Engineers build and maintain data pipelines. This course may be useful for those looking to enter this field. You will learn how to use R to work with big data.

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Software Engineer

Software Engineers design, develop, and maintain software systems. This course may be useful for those looking to enter this field. You will learn the fundamentals of R, which is a popular programming language for data science.

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Computer Scientist

Computer Scientists conduct research in computer science. This course may be useful for those looking to enter this field. You will learn the fundamentals of R, which is a popular programming language for data science.

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Data Visualization Specialist

Data Visualization Specialists create visualizations to communicate data insights. This course may be useful for those looking to enter this field. You will learn how to use R to create visualizations.

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Database Administrator

Database Administrators manage and maintain databases. This course may be useful for those looking to enter this field. You will learn how to use R to work with data in databases.

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Information Security Analyst

Information Security Analysts protect computer systems and networks from attack. This course may be useful for those looking to enter this field. You will learn the fundamentals of R, which is a popular programming language for data science.

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