Johns Hopkins University
Tidyverse Skills for Data Science in R Specialization
Johns Hopkins University

Tidyverse Skills for Data Science in R Specialization

Develop Insights from Data With Tidy Tools. Import, wrangle, visualize, and model data with the Tidyverse R packages

Taught in English

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Stephanie Hicks, PhD
Shannon Ellis, PhD
Carrie Wright, PhD

Instructors: Stephanie Hicks, PhD

2,902 already enrolled

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Specialization - 5 course series

Get in-depth knowledge of a subject

4.6

(86 reviews)

Beginner level

Recommended experience

2 months at 10 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Organize a data science project

  • Import data from common spreadsheet, database, and web-based formats

  • Wrangle and manipulate messy data and build tidy datasets

  • Build presentation quality data graphics

  • Build predictive machine learning models

Details to know

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Specialization - 5 course series

Get in-depth knowledge of a subject

4.6

(86 reviews)

Beginner level

Recommended experience

2 months at 10 hours a week
Flexible schedule
Learn at your own pace

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Specialization - 5 course series

Introduction to the Tidyverse

Course 17 hours4.3 (40 ratings)

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

Importing Data in the Tidyverse

Course 215 hours4.7 (42 ratings)

What you'll learn

  • Describe different data formats

  • Apply Tidyverse functions to import data into R from external formats

  • Obtain data from a web API

Skills you'll gain

Category: Data Management
Category: Data Visualization
Category: R Programming
Category: tidying data

Wrangling Data in the Tidyverse

Course 314 hours4.5 (31 ratings)

What you'll learn

  • Apply Tidyverse functions to transform non-tidy data to tidy data

  • Conduct basic exploratory data analysis

  • Conduct analyses of text data

Visualizing Data in the Tidyverse

Course 416 hours4.7 (20 ratings)

What you'll learn

  • Distinguish between various types of plots and their uses

  • Use the ggplot2 R package to develop data visualizations

  • Build effective data summary tables

  • Build data animations for visual storytelling

What you'll learn

  • Describe different types of data analytic questions

  • Conduct hypothesis tests of your data

  • Apply linear modeling techniques to answer multivariable questions

  • Apply machine learning workflows to detect complex patterns in your data

Instructors

Stephanie Hicks, PhD
Johns Hopkins University
5 Courses5,560 learners
Shannon Ellis, PhD
Johns Hopkins University
5 Courses5,560 learners

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