This course introduces the R programming language and is designed for beginners who are new to R and coding. Specific topics covered include using RStudio and writing documents with with Quarto along with basic coding principles, defining variables, vectors, and data frames, pipes, data manipulation with DDPLYR, and data visualization with GGPLOT2.

This course provides an opportunity to practice your R skills by cleaning a real world dataset, while learning best practices for conducting reproducible data cleaning. Specific topics covered include identifying and addressing missing values, handling data quality issues, and transforming raw data into a clean and structured format ready for analysis.

This course introduces the Python programming language, with a focus on using Python for data analysis, and is designed for beginners who are new to Python and coding. Specific topics covered include using VS Code and working with Jupyter notebooks along with basic coding principles, defining variables, loading libraries, working with Pandas DataFrames, and visualizing data using the seaborn library.