AI Academy

Data Visualization and Transformation with R

Instructor: Mine Çetinkaya-Rundel , Dr. Elijah Meyer Duration: 1 week to complete at 10 hours a week
Objective 1 Transform, visualize, summarize, and analyze data in R, with packages from the Tidyverse, using RStudio
Objective 2 Carry out analyses in a reproducible and shareable manner with Quarto
Objective 3 Learn to effectively communicate results through an optional written project version controlled with Git and hosted on GitHub
R Programming
Data-Driven Decision-Making
Data Visualization Software
Data Science
Statistical Analysis
Data analysis
Git (Version Control System)
Descriptive Statistics
Data Manipulation
Data Transformation
Data Visualization
Statistics
Probability & Statistics
Exploratory Data Analysis
Tidyverse (R Package)
Data Wrangling
Statistical Programming
Ggplot2
GitHub

Data Tidying and Importing with R

Instructor: Dr. Elijah Meyer , Mine Çetinkaya-Rundel Duration: 1 week to complete at 10 hours a week
Objective 1 Apply tidy data principles to manipulate and restructure data (e.g., subsetting, adding columns, and transforming data between wide and long formats)
Objective 2 Develop and implement code to join data sets and perform basic web scraping to collect data
Objective 3 Apply data structures such as wide and long formats, using code to convert between these formats as part of data preparation and analysis
Data Cleansing
Data Literacy
Data Ethics
Data Transformation
Data Import/Export
Exploratory Data Analysis
R Programming
Tidyverse (R Package)
Web Scraping
Data Wrangling
Data Manipulation

Data Science Ethics with R

Instructor: Mine Çetinkaya-Rundel , Dr. Elijah Meyer Duration: 6 hours to complete 3 weeks at 2 hours a week
Objective 1 Critically assess ethical concerns considering data intent and data privacy
Objective 2 Identify strategies that can be incorporated to help secure sensitive data
Objective 3 Define algorithmic bias and become conscious of when these situations may occur
Algorithms
Data Quality
R Programming
Data Literacy
Data Ethics
Data Visualization Software
Data Presentation
Data Integrity
Data Collection