DataScience Classroom

Tools for DataScience Classroom

To generate and organize class materials for data science programs, I use R Markdown. RMarkdown allows me to share relevant information with students in various formats, enabling learners to master essential skills at their own pace.

R Markdown serves as a notebook interface, seamlessly integrating narrative text and code to produce well-formatted output. It supports multiple languages, including R, Python, and SQL. Additionally, it emphasizes the creation of fully reproducible documents, enabling immersive learning through the reproduction of codes, graphs, equations, and more. R Markdown also offers dynamic output formats such as HTML, PDF, MS Word, Beamer, HTML5 slides, Tufte-style handouts, books, dashboards, shiny applications, scientific articles.

For example, for the subject of the program: BigData & Data Analysis for the I divided four modules in Rmarkdown document, in html format-,and them used the same information with Beamer presentation format. The outputs were:

For instance, in the Big Data & Data Analysis program at Siglo 21 University, I divided the course into four modules within an RMarkdown document, presented in HTML format. I also utilized the same information to create a Beamer presentation format. The outputs were as follows:

Modules	RMarkdown documents
Module 1 Introduction Data Analysis and Big Data	https://rpubs.com/MaraD/Modulo1AnalisisdeDatos
Module 2 Data Cleaning	https://rpubs.com/MaraD/modulo2AnalisisdeDatos
Module 3 Data Exploration	https://rpubs.com/MaraD/Modulo3AnalisisdeDatos
Module 4: Insight Generation	https://rpubs.com/MaraD/Modulo4AnalisisdeDatos

Publishing

I shared it on RPubs because it is a free and user-friendly platform.