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

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

Instructors: Stephanie Hicks, PhD

Sponsored by RIA PAYMENT INSTITUTION

3,249 already enrolled

Get in-depth knowledge of a subject
4.6

(90 reviews)

Beginner level

Recommended experience

2 months
at 10 hours a week
Flexible schedule
Learn at your own pace
Get in-depth knowledge of a subject
4.6

(90 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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Taught in English

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Specialization - 5 course series

Introduction to the Tidyverse

Course 17 hours4.4 (42 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

Skills you'll gain

Category: R Programming
Category: Tidyverse (R Package)
Category: Data Transformation
Category: Data Processing
Category: Data Wrangling
Category: Document Management
Category: Information Management
Category: Data Analysis
Category: Operating Systems
Category: File Systems
Category: Statistical Programming
Category: Data Mapping
Category: Extract, Transform, Load
Category: Data Validation
Category: Data Storage
Category: Data Integration
Category: Data Manipulation
Category: Data Engineering
Category: Data Science
Category: Data Cleansing

Importing Data in the Tidyverse

Course 215 hours4.7 (44 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: R Programming
Category: Tidyverse (R Package)
Category: Databases
Category: Data Import/Export
Category: Data Integration
Category: Extract, Transform, Load
Category: Web Scraping
Category: JSON
Category: Application Programming Interface (API)
Category: Spreadsheet Software
Category: Relational Databases
Category: Database Systems
Category: Data Transformation
Category: Data Processing
Category: Extensible Languages and XML
Category: Extensible Markup Language (XML)
Category: Statistical Programming
Category: Data Wrangling
Category: Data Engineering
Category: YAML

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

Skills you'll gain

Category: Tidyverse (R Package)
Category: R Programming
Category: Statistical Programming
Category: Data Transformation
Category: Data Processing
Category: Data Wrangling
Category: Advanced Analytics
Category: Exploratory Data Analysis
Category: Data Manipulation
Category: Statistical Analysis
Category: Statistics
Category: Data Engineering
Category: Extract, Transform, Load
Category: Data Mapping
Category: Data Integration
Category: Data Science
Category: Unstructured Data
Category: Text Mining
Category: Data Analysis
Category: Analytics

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

Skills you'll gain

Category: Data Visualization
Category: Statistical Visualization
Category: Data Visualization Software
Category: Exploratory Data Analysis
Category: Plot (Graphics)
Category: Data Presentation
Category: Ggplot2
Category: R Programming
Category: Interactive Data Visualization
Category: Statistical Analysis
Category: Statistical Methods
Category: Dashboard
Category: Statistics
Category: Analytics
Category: Statistical Programming
Category: Data Science
Category: Tidyverse (R Package)
Category: Probability & Statistics
Category: Data Analysis
Category: Data 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

Skills you'll gain

Category: Statistical Modeling
Category: Data Analysis
Category: Statistical Analysis
Category: Data Science
Category: Statistics
Category: Statistical Methods
Category: Predictive Analytics
Category: Predictive Modeling
Category: Mathematical Modeling
Category: Regression Analysis
Category: Analytics
Category: Statistical Inference
Category: Tidyverse (R Package)
Category: Exploratory Data Analysis
Category: R Programming
Category: Business Analytics
Category: Advanced Analytics
Category: Statistical Programming
Category: Applied Machine Learning
Category: Statistical Machine Learning

Instructors

Stephanie Hicks, PhD
Johns Hopkins University
5 Courses6,166 learners
Shannon Ellis, PhD
Johns Hopkins University
5 Courses6,166 learners

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