DataScience Classroom


Mara Destéfanis


April 15, 2023

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
Module 2 Data Cleaning
Module 3 Data Exploration
Module 4: Insight Generation


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