Johns Hopkins University
Data Science: Foundations using R Specialization
Johns Hopkins University

Data Science: Foundations using R Specialization

Roger D. Peng, PhD
Brian Caffo, PhD
Jeff Leek, PhD

Instructors: Roger D. Peng, PhD

Sponsored by RIA PAYMENT INSTITUTION

110,807 already enrolled

Get in-depth knowledge of a subject
4.6

(6,101 reviews)

Beginner level
No prior experience required
4 months
at 10 hours a week
Flexible schedule
Learn at your own pace
Get in-depth knowledge of a subject
4.6

(6,101 reviews)

Beginner level
No prior experience required
4 months
at 10 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Use R to clean, analyze, and visualize data.

  • Learn how to ask the right questions, obtain data, and perform reproducible research.

  • Use GitHub to manage data science projects.

Details to know

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Taught in English

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  • Learn in-demand skills from university and industry experts
  • Master a subject or tool with hands-on projects
  • Develop a deep understanding of key concepts
  • Earn a career certificate from Johns Hopkins University
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Specialization - 5 course series

The Data Scientist’s Toolbox

Course 117 hours4.6 (33,960 ratings)

What you'll learn

  • Set up R, R-Studio, Github and other useful tools

  • Understand the data, problems, and tools that data analysts use

  • Explain essential study design concepts

  • Create a Github repository

Skills you'll gain

Category: R Programming
Category: Rmarkdown
Category: Git (Version Control System)
Category: Statistical Programming
Category: Software Configuration Management
Category: GitHub
Category: Version Control
Category: Software Development Tools
Category: Data Science
Category: Software Versioning
Category: Data Analysis
Category: General Science and Research
Category: Research
Category: Research Design
Category: Experimentation
Category: Scientific Methods
Category: Software Development
Category: Configuration Management
Category: Statistical Machine Learning
Category: Research Methodologies

R Programming

Course 257 hours4.5 (22,265 ratings)

What you'll learn

  • Understand critical programming language concepts

  • Configure statistical programming software

  • Make use of R loop functions and debugging tools

  • Collect detailed information using R profiler

Skills you'll gain

Category: Data Science
Category: R Programming
Category: Data Analysis
Category: Statistical Programming
Category: Computer Science
Category: Computer Programming
Category: Data Manipulation
Category: Computer Programming Tools
Category: Simulations
Category: Machine Learning
Category: Application Performance Management
Category: Engineering Software
Category: Performance Tuning
Category: Software Engineering
Category: Software Development Tools
Category: Programming Principles
Category: Software Development
Category: Simulation and Simulation Software
Category: Debugging
Category: Statistical Machine Learning

Getting and Cleaning Data

Course 319 hours4.5 (8,065 ratings)

What you'll learn

  • Understand common data storage systems

  • Apply data cleaning basics to make data "tidy"

  • Use R for text and date manipulation

  • Obtain usable data from the web, APIs, and databases

Skills you'll gain

Category: R Programming
Category: Statistical Programming
Category: Data Analysis
Category: Data Science
Category: Data Manipulation
Category: Data Processing
Category: Web Scraping
Category: Data Engineering
Category: Data Architecture
Category: Data Import/Export
Category: Tidyverse (R Package)
Category: Data Integration
Category: Big Data
Category: Data Quality
Category: Data Wrangling
Category: Data Collection
Category: Data Transformation
Category: Data Access
Category: Databases
Category: Extract, Transform, Load

Exploratory Data Analysis

Course 454 hours4.7 (6,071 ratings)

What you'll learn

  • Understand analytic graphics and the base plotting system in R

  • Use advanced graphing systems such as the Lattice system

  • Make graphical displays of very high dimensional data

  • Apply cluster analysis techniques to locate patterns in data

Skills you'll gain

Category: Statistical Visualization
Category: Plot (Graphics)
Category: Data Visualization Software
Category: Data Visualization
Category: Exploratory Data Analysis
Category: Data Presentation
Category: Data Analysis
Category: Ggplot2
Category: R Programming
Category: Dashboard
Category: Statistical Methods
Category: Analytics
Category: Data Storytelling
Category: Statistics
Category: Data Science
Category: Dimensionality Reduction
Category: Unsupervised Learning
Category: Interactive Data Visualization
Category: Statistical Analysis
Category: Statistical Programming

Reproducible Research

Course 57 hours4.6 (4,174 ratings)

What you'll learn

  • Organize data analysis to help make it more reproducible

  • Write up a reproducible data analysis using knitr

  • Determine the reproducibility of analysis project

  • Publish reproducible web documents using Markdown

Skills you'll gain

Category: Rmarkdown
Category: R Programming
Category: Knitr
Category: Research Methodologies
Category: Technical Communication
Category: Scientific Methods
Category: Quality Assurance and Control
Category: Technical Writing
Category: Quality Assurance
Category: Verification And Validation
Category: Information Management
Category: Data Management
Category: Data Analysis
Category: Data Sharing
Category: Research
Category: Data Governance
Category: General Science and Research
Category: Data Science
Category: Statistical Programming
Category: Product Quality (QA/QC)

Instructors

Roger D. Peng, PhD
Johns Hopkins University
37 Courses1,617,030 learners
Brian Caffo, PhD
Johns Hopkins University
30 Courses1,643,354 learners

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