Introduction to the Tidyverse
About this Course
This course introduces a powerful set of data science tools known as the Tidyverse. The Tidyverse has revolutionized the way in which data scientists do almost every aspect of their job. We will cover the simple idea of \"tidy data\" and how this idea serves to organize data for analysis and modeling. We will also cover how non-tidy can be transformed to tidy data, the data science project life cycle, and the ecosystem of Tidyverse R packages that can be used to execute a data science project. 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.Created by: Johns Hopkins University

Related Online Courses
This course is designed for novice learners wanting to understand the basics of ISO and IEC security standards. Learners will gain understanding how security standards address the challenges facing... more
In this course, you will see how to use advanced machine-learning techniques to build more sophisticated recommender systems. Machine Learning is able to provide recommendations and make better... more
In the rapidly evolving realm of game development, the transition from foundational concepts to mastering advanced platforms like Unreal Engine marks a pivotal journey for beginners and... more
The objective of this course is to support urban water and sanitation utilities in transitioning to climate-resilient management by reducing their carbon emissions. This course, consisting of 4... more
Discrete Mathematics is the language of Computer Science. One needs to be fluent in it to work in many fields including data science, machine learning, and software engineering (it is not a... more