This Specialization is intended for data scientists with some familiarity with the R programming language who are seeking to do data science using the Tidyverse family of packages. Through 5 courses, you will cover importing, wrangling, visualizing, and modeling data using the powerful Tidyverse framework. The Tidyverse packages provide a simple but powerful approach to data science which scales from the most basic analyses to massive data deployments. This course covers the entire life cycle of a data science project and presents specific tidy tools for each stage.
Tidyverse Skills for Data Science in R Specialization
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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
Instructors: Carrie Wright, PhD
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Get in-depth knowledge of a subject
(98 reviews)
Beginner level
Recommended experience
2 months at 10 hours a week
Flexible schedule
Earn a career credential
Share your expertise with employers
Get in-depth knowledge of a subject
(98 reviews)
Beginner level
Recommended experience
2 months at 10 hours a week
Flexible schedule
Earn a career credential
Share your expertise with employers
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
Overview
Skills you'll gain
- Data Import/Export
- Data Analysis Software
- Exploratory Data Analysis
- Web Scraping
- Statistical Hypothesis Testing
- Data Analysis
- Tidyverse (R Package)
- Statistical Modeling
- Data Science
- Data Manipulation
- Data Visualization
- Statistical Visualization
- Predictive Modeling
- Data Cleansing
- Data Wrangling
- Data Visualization Software
- Data Modeling
- Plot (Graphics)
Tools you'll learn
What’s included
Shareable certificate
Add to your LinkedIn profile
Taught in English
31 practice exercises
Advance your subject-matter expertise
- Learn in-demand skills from university and industry experts
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- Earn a career certificate from Johns Hopkins University
Specialization - 5 course series
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: Data Wrangling
Category: Tidyverse (R Package)
Category: File Management
Category: Data Manipulation
Category: Data Analysis
Category: Exploratory Data Analysis
Category: R Programming
Category: Data Cleansing
Category: Data Import/Export
Category: Data Science
Category: Ggplot2
Category: Data Visualization
Category: Data Management
Category: Data Transformation
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 Import/Export
Category: Tidyverse (R Package)
Category: R Programming
Category: Relational Databases
Category: Google Sheets
Category: Data Manipulation
Category: Web Scraping
Category: Data Integration
Category: Data Storage
Category: Spreadsheet Software
Category: Databases
Category: Data Transformation
Category: Extensible Markup Language (XML)
Category: Unstructured Data
Category: SQL
Category: Application Programming Interface (API)
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: Data Wrangling
Category: Tidyverse (R Package)
Category: Data Manipulation
Category: Data Transformation
Category: R Programming
Category: Text Mining
Category: Time Series Analysis and Forecasting
Category: Exploratory Data Analysis
Category: Data Processing
Category: Data Cleansing
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: Ggplot2
Category: Scatter Plots
Category: Histogram
Category: Data Visualization Software
Category: Tidyverse (R Package)
Category: R Programming
Category: Animations
Category: Data Storytelling
Category: Statistical Visualization
Category: Data Manipulation
Category: Exploratory Data Analysis
Category: Data Presentation
Category: Plot (Graphics)
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: Regression Analysis
Category: Tidyverse (R Package)
Category: R Programming
Category: Statistical Inference
Category: Statistical Hypothesis Testing
Category: Data Analysis
Category: Statistical Modeling
Category: Data Science
Category: Predictive Modeling
Category: Rmarkdown
Category: Statistical Analysis
Category: Data-Driven Decision-Making
Category: Classification And Regression Tree (CART)
Category: Data Modeling
Category: Machine Learning
Category: Statistical Methods
Category: Exploratory Data Analysis
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Frequently asked questions
This Specialization will take approximately 12-15 weeks.
Some familiarity with the R programming language is required.
The courses are cumulative, so it is recommended that students take the courses in order.
More questions
Financial aid available,