Análisis de datos con R Programming y Python

Análisis de datos con R Programming y Python – DataBoosters Academy
Updated July 2026

Explore the free Análisis de datos con R Programming y Python Udemy course, taught by DataBoosters Academy. This online course blends R and Python to teach practical data‑science skills, from cleaning dataframes to building predictive models. Learners gain hands‑on experience with visualizations, regression, time‑series forecasting, and text analysis, earning a certificate that validates their new expertise. Ideal for anyone searching “free data analysis course” or “learn data analysis online,” the curriculum stays current with industry‑standard tools.

What You'll Learn

• Build clean and well‑structured dataframes in R and Python using dplyr and pandas.
• Master advanced data visualizations with ggplot2, Pyplot, and interactive chart libraries.
• Learn multiple linear regression techniques and apply them to real‑world business problems.
• Understand time‑series analysis, seasonal decomposition, and forecasting with ARIMA models.
• Create efficient matrix operations using NumPy for high‑performance scientific computing.
• Implement regular expressions (regex) to extract insights from unstructured text data.
• Apply data‑driven storytelling by turning analytical results into compelling visual reports.
• Analyze how R and Python complement each other in a modern data‑science workflow.

Course Details

• Instructor: DataBoosters Academy
• Rating: 4.4 stars
• Language: Español (es‑LA)
• Last updated: July 2026
• Certificate: Yes, upon completion
• Includes: Lifetime access, Mobile‑friendly learning

What This Course Covers

Parte 1 – R Programming Fundamentals

• Manipulación de dataframes con dplyr y tidyr.
• Técnicas de limpieza de datos: detección y tratamiento de valores faltantes.
• Creación de gráficos avanzados con ggplot2 para identificar patrones.
• Modelado de regresión lineal múltiple y evaluación de supuestos estadísticos.

Parte 2 – Python for Data Science

• Operaciones vectorizadas y manipulación de matrices usando NumPy.
• Visualizaciones impactantes con Matplotlib Pyplot y personalización de estilos.
• Análisis de datos estructurados mediante pandas: filtrado, agrupación y transformación.
• Uso de expresiones regulares (regex) para extracción de información de texto.

Análisis de Series de Tiempo

• Introducción a series temporales y componentes estacionales.
• Aplicación de modelos ARIMA y pronósticos con datos económicos.
• Evaluación de precisión mediante métricas como MAE y RMSE.

Proyecto Final Integrado

• Importación y limpieza de un conjunto de datos real.
• Exploración visual combinando gráficos de R y Python.
• Construcción de modelo predictivo y presentación de resultados.

Herramientas y Entorno de Trabajo

• Configuración de RStudio y Jupyter Notebook para desarrollo colaborativo.
• Gestión de paquetes con conda y install.packages().
• Uso de Git para control de versiones y reproducibilidad.

Buenas Prácticas en Ciencia de Datos

• Principios de reproducibilidad y documentación del flujo de trabajo.
• Estrategias de validación cruzada y selección de características.
• Ética en el manejo de datos y consideraciones de privacidad.

Who Should Take This Course

• Beginners in data science who need a solid foundation in R and Python.
• Business analysts looking to automate reporting with statistical programming.
• Researchers and academics requiring robust tools for data cleaning and visualization.
• Mid‑level professionals aiming to upgrade to advanced modeling and time‑series analysis.
• Students preparing for data‑science certifications that require proficiency in both languages.

Prerequisites

• No prior programming experience needed — the course is beginner‑friendly.
• Basic familiarity with spreadsheets (Excel, Google Sheets) is helpful but optional.
• Recommended: a curiosity for turning raw data into actionable insights.

Why Enroll in This Course

Enroll now to access a free coupon that makes this comprehensive Udemy course 100 % off for a limited time. The curriculum blends theory with real‑world projects, ensuring you can apply learned techniques immediately. Compared with other data‑analysis trainings, this course offers dual‑language instruction, lifetime access, and a certificate that boosts your résumé. Act before the coupon expires to start learning without any financial barrier.

Course Highlights

• Lifetime access to all video lectures and downloadable resources.
• Self‑paced learning lets you study whenever and wherever you prefer.
• Certificate of completion validates your new R and Python data‑analysis skills.
• Mobile‑friendly platform enables learning on smartphones and tablets.
• Hands‑on projects simulate real business scenarios for practical experience.
• Community support through Udemy Q&A and peer discussions.

Frequently Asked Questions

Q: Is this course really free?
A: Yes. A free coupon provides 100 % off the regular price, allowing you to enroll at no cost while the offer lasts.

Q: What will I learn in this data analysis course?
A: You will master data cleaning, visualization, regression, time‑series forecasting, and text mining using both R and Python, plus best practices for reproducible workflows.

Q: Do I get a certificate after completing this course?
A: Upon finishing all modules and the final project, Udemy issues a certificate that confirms your proficiency in R and Python data analysis.

Q: Is this course suitable for beginners?
A: Absolutely. The curriculum starts with fundamental concepts and progressively introduces advanced techniques, making it ideal for newcomers and seasoned analysts alike.

Q: How long do I have to enroll for free?
A: The free coupon is available for a limited period; enroll as soon as possible to secure the 100 % discount before it expires.

Final Thoughts

Análisis de datos con R Programming y Python equips beginners and professionals alike with