Ementorhub

What you'll learn

Transform, visualize, summarize, and analyze data in R, with packages from the Tidyverse, using RStudio

Carry out analyses in a reproducible and shareable manner with Quarto

Learn to effectively communicate results through an optional written project version controlled with Git and hosted on GitHub

Skills you'll gain

Data Analysis

Data Transformation

Statistical Programming

Data Visualization

Ggplot2

Data Manipulation

Data Visualization Software

Statistical Methods

Data Science

Git (Version Control System)

Version Control

GitHub

Data Cleansing

Data-Driven Decision-Making

R Programming

Statistical Analysis

Exploratory Data Analysis

Tidyverse (R Package)

There are 3 modules in this course

This course is an introduction to data science and statistical thinking. Learners will gain experience with exploring, visualizing, and analyzing data to understand natural phenomena and investigate patterns, model outcomes, and do so in a reproducible and shareable manner. Topics covered include data visualization and transformation for exploratory data analysis. Learners will be introduced to problems and case studies inspired by and based on real-world questions and data via lecture and live coding videos as well as interactive programming exercises. The course will focus on the R statistical computing language with a focus on packages from the Tidyverse, the RStudio integrated development environment, Quarto for reproducible reporting, and Git and GitHub for version control. The skills learners will gain in this course will prepare them for careers in a variety of fields, including data scientist, data analyst, quantitative analyst, statistician, and much more.

Data and Visualization

Visualizing, transforming, and summarizing types of data