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 ARS SCINet/AI-COE

109,720 already enrolled

Get in-depth knowledge of a subject
4.6

(6,080 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

(6,080 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 (33,933 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: Data Analysis
Category: Data Management
Category: Computer Programming
Category: Computer Programming Tools
Category: Data Analysis Software
Category: Programming Principles
Category: Statistical Programming

R Programming

Course 257 hours4.5 (22,245 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: Computer Programming
Category: Computer Programming Tools
Category: Critical Thinking
Category: Data Analysis
Category: Data Structures
Category: Problem Solving
Category: Programming Principles
Category: Statistical Programming
Category: General Statistics

Getting and Cleaning Data

Course 319 hours4.5 (8,062 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: Computer Programming
Category: Data Analysis
Category: Data Management
Category: Databases
Category: Statistical Programming
Category: Data Structures

Exploratory Data Analysis

Course 454 hours4.7 (6,068 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: Computer Graphic Techniques
Category: Computer Graphics
Category: Data Analysis
Category: Statistical Programming
Category: Data Visualization

Reproducible Research

Course 57 hours4.6 (4,173 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: Communication
Category: Computer Programming
Category: Computer Programming Tools
Category: Data Analysis
Category: Programming Principles
Category: Statistical Programming

Instructors

Roger D. Peng, PhD
Johns Hopkins University
37 Courses1,608,001 learners
Brian Caffo, PhD
Johns Hopkins University
30 Courses1,633,988 learners

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