Introducción a Data Science: Programación Estadística con R

Go to Course: https://www.coursera.org/learn/intro-data-science-programacion-estadistica-r

Introduction

**Course Review: Introducción a Data Science: Programación Estadística con R on Coursera** As the world becomes increasingly data-driven, having the skills to analyze and interpret data is more important than ever. If you're looking to start your journey in data science, "Introducción a Data Science: Programación Estadística con R" on Coursera is an excellent choice. This course provides a solid foundation in R, the go-to programming language for statistical analysis, and enables you to begin manipulating and analyzing quantitative data with ease. ### Overview The course is designed to take beginners through the basics of R programming, focusing on statistical applications. You'll learn how to read and manipulate data, perform analyses, and visualize results using R's powerful capabilities. By the end of the course, students will not only be comfortable with R programming but also be equipped with the skills necessary to tackle real-world data challenges. ### Key Features 1. **Installation of Tools**: The course kicks off with a friendly introduction to the tools necessary for programming in R. It thoughtfully covers the installation process on various operating systems (Windows, Linux, and Mac OS), making it accessible to everyone. 2. **Introduction to the Language**: In the first week, learners will get acquainted with the essentials of R programming. This includes understanding objects, classes, and data types. The ability to read and write data from various sources is also a crucial skill covered during this week. 3. **Utilization of the Language**: In the following week, you'll dive into more complex functionalities of R. This includes control structures to streamline repetitive tasks, creating functions for specific operations, managing dates, and employing vectorized operations to enhance the efficiency of your code. The course emphasizes writing clean, stylish code, which is important for collaboration and maintenance. 4. **Graphing with R's Graphics System**: As data visualization can significantly impact how information is communicated, the course dedicates a week to exploring R's graphics system. You'll learn about vectorized functions and how to modify graphical outputs, ensuring you can present your data compellingly. 5. **Regular Expressions, ggplot2, and Simulation**: The final week focuses on advanced topics like regular expressions for text processing, data visualization using the ggplot2 package, and simulation to model data trends. You'll troubleshoot common errors and refine your skills in data presentation. ### Recommendations "Introducción a Data Science: Programación Estadística con R" is highly recommended for anyone interested in data science, statistics, or programming. Here are some reasons why you should consider enrolling: - **Beginner-Friendly**: The course structure is straightforward and gradually builds complexity, which is ideal for those new to programming. - **Hands-On Learning**: With practical exercises and real data sets, you'll get the experience required to apply your knowledge immediately. - **Community and Support**: Enrolling in a Coursera course provides you with access to a supportive community of learners and educators who can assist you along the way. - **Enhanced Career Prospects**: Data science skills are in high demand. Completing this course will enhance your resume and open new career opportunities in various industries. ### Conclusion In summary, "Introducción a Data Science: Programación Estadística con R" offers a comprehensive introduction to R programming and data analysis. It equips you with the foundational skills necessary to start a career in data science or to augment your current role with valuable analytical capabilities. Whether you're a student, a professional looking to shift careers, or simply someone with a passion for data, this course is a worthy investment in your future. Don’t miss the opportunity to learn from the experts and become proficient in one of the most respected programming languages in data science. Happy learning!

Syllabus

Instalación de Herramientas

Una pequeña introducción a lo que veremos en el curso y la instalación de las herramientas a usar en él, tanto para sistemas operativos Windows, Linux y Mac OS.

En esta primera semana, tendrás tus primeros pasos en el lenguaje, entenderás que son los objetos, las clases, los tipos de datos y podrás leer y escribir datos a distintas fuentes y tipos de archivos.

En esta semana, aprenderás a utilizar las estructuras de control para agilizar tareas repetitivas, a crear funciones para llevar a cabo tareas específicas o complejas, las reglas de alcance, el manejo de las fechas y variables de fechas, la importancia de utilizar operaciones vectorizadas para hacer tu código más rápido, por qué es importante escribir código con un buen estilo.

En esta semana primero conocerás una familia de funciones vectorizadas, las cuales te permitirán efectuar operaciones con muy pocas líneas de código, después conocerás el sistema de gráficos y las funciones que permiten realizar modificaciones en él.

Ensta última semana aprenderás sobre expresiones regulares y cómo utilizarlas con R, graficarás con el paquete de gráficos ggplot2, entenderás cómo encontrar errores y arreglarlos y llevarás a cabo simulación.