About this course: In this course you will learn how to program in R and how to use R for effective data analysis. You will learn how to install and configure software necessary for a statistical programming environment and describe generic programming language concepts as they are implemented in a high-level statistical language. The course covers practical issues in statistical computing which includes programming in R, reading data into R, accessing R packages, writing R functions, debugging, profiling R code, and organizing and commenting R code. Topics in statistical data analysis will provide working examples.
Who is this class for: Some programming experience (in any language) is recommended.
Created by: Johns Hopkins University
Taught by: Roger D. Peng, PhD, Associate Professor, Biostatistics
Bloomberg School of Public Health
Taught by: Jeff Leek, PhD, Associate Professor, Biostatistics
Bloomberg School of Public Health
Taught by: Brian Caffo, PhD, Professor, Biostatistics
Bloomberg School of Public Health
| Basic Info |
Course 2 of 10 in the
Data Science Specialization.
|
| Level | Intermediate |
| Language | English, Subtitles: French, Japanese, Chinese (Simplified) |
| How To Pass | Pass all graded assignments to complete the course. |
| User Ratings |
Syllabus
WEEK 1
Week 1: Background, Getting Started, and Nuts & Bolts
This week covers the basics to get you started up with R. The Background Materials lesson contains information about course mechanics and some videos on installing R. The Week 1 videos cover the history of R and S, go over the basic data types in R, and descri...
28 videos, 9 readings
Graded: Week 1 Quiz
WEEK 2
Week 2: Programming with R
Welcome to Week 2 of R Programming. This week, we take the gloves off, and the lectures cover key topics like control structures and functions. We also introduce the first programming assignment for the course, which is due at the end of the week.
13 videos, 3 readings
Graded: Week 2 Quiz
Graded: Programming Assignment 1: Quiz
WEEK 3
Week 3: Loop Functions and Debugging
We have now entered the third week of R Programming, which also marks the halfway point. The lectures this week cover loop functions and the debugging tools in R. These aspects of R make R useful for both interactive work and writing longer code, and so they a...
8 videos, 2 readings
Graded: Week 3 Quiz
Graded: Programming Assignment 2: Lexical Scoping
WEEK 4
Week 4: Simulation & Profiling
This week covers how to simulate data in R, which serves as the basis for doing simulation studies. We also cover the profiler in R which lets you collect detailed information on how your R functions are running and to identify bottlenecks that can be addresse...
6 videos, 4 readings
Graded: Week 4 Quiz
Graded: Programming Assignment 3: Quiz
FAQs
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Coursework
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Creators
Johns Hopkins University
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Pricing
| Audit | Purchase Course | |
|---|---|---|
| Access to course materials | Available | Available |
| Access to graded materials | Not available | Available |
| Receive a final grade | Not available | Available |
| Earn a shareable Course Certificate | Not available | Available |
Ratings and Reviews
I am working as BI and using R almost every day.Thank you for this course.
I can say that it very powerful tool for data analysis, especially big datasets.
I found the material presented in this course to be extremely informative and useful. I would highly recommend this course to anyone that wants to become more familiar with R.
The course is too basic.
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This course is easy at the beggining. And difficult at the end. I try to do it at least 2. I will recommend it to all the people who would like to get knowledge in programming and in data science. To these who are curious about the world.