Ementorhub

What you'll learn

Distinguish between tidy and non-tidy data

Describe how non-tidy data can be transformed into tidy data

Describe the Tidyverse ecosystem of packages

Organize and initialize a data science project

Skills you'll gain

Data Manipulation

Data Transformation

Data Import/Export

Data Wrangling

Ggplot2

Data Analysis

Tidyverse (R Package)

R Programming

File Management

Data Cleansing

Exploratory Data Analysis

Data Science

There are 6 modules in this course

If you are new to data science, the Tidyverse ecosystem of R packages is an excellent way to learn the different aspects of the data science pipeline, from importing the data, tidying the data into a format that is easy to work with, exploring and visualizing the data, and fitting machine learning models. If you are already experienced in data science, the Tidyverse provides a power system for streamlining your workflow in a coherent manner that can easily connect with other data science tools. In this course it is important that you be familiar with the R programming language. If you are not yet familiar with R, we suggest you first complete R Programming before returning to complete this course.

From Non-Tidy –> Tidy

The Data Science Life Cycle & Tidyverse Ecosystem

Data Science Project Organization & Workflows

Case Studies

Project: Organizing a New Data Science Project