About this course: This course covers advanced topics in R programming that are necessary for developing powerful, robust, and reusable data science tools. Topics covered include functional programming in R, robust error handling, object oriented programming, profiling and benchmarking, debugging, and proper design of functions. Upon completing this course you will be able to identify and abstract common data analysis tasks and to encapsulate them in user-facing functions. Because every data science environment encounters unique data challenges, there is always a need to develop custom software specific to your organization’s mission. You will also be able to define new data types in R and to develop a universe of functionality specific to those data types to enable cleaner execution of data science tasks and stronger reusability within a team.

Created by: Johns Hopkins University

Taught by: Roger D. Peng, PhD, Associate Professor, Biostatistics
Bloomberg School of Public Health
Taught by: Brooke Anderson, Assistant Professor, Environmental & Radiological Health Sciences
Colorado State University

Basic Info	Course 2 of 5 in the Mastering Software Development in R Specialization.
Level	Intermediate
Language	English, Subtitles: Chinese (Simplified)
How To Pass	Pass all graded assignments to complete the course.
User Ratings	4.4 stars Average User Rating 4.4See what learners said

Syllabus

WEEK 1

Welcome to Advanced R Programming

This course covers advanced topics in R programming that are necessary for developing powerful, robust, and reusable data science tools. Topics covered include functional programming in R, robust error handling, object oriented programming, profiling and bench...

1 video, 3 readings

Functions

This module begins with control structures in R for controlling the logical flow of an R program. We then move on to functions, their role in R programming, and some guidelines for writing good functions.

17 readings

Graded: Swirl Lesson

WEEK 2

Functional Programming

Functional programming is a key aspect of R and is one of R's differentiating factors as a data analysis language. Understanding the concepts of functional programming will help you to become a better data science software developer. In addition, we cover erro...

19 readings

Graded: Swirl Lesson

WEEK 3

Debugging and Profiling

Debugging tools are useful for analyzing your code when it exhibits unexpected behavior. We go through the various debugging tools in R and how they can be used to identify problems in code. Profiling tools allow you to see where your code spends its time and ...

15 readings

Graded: Debugging and Profiling

WEEK 4

Object-Oriented Programming

Object oriented programming allows you to define custom data types or classes and a set of functions for handling that data type in a way that you define. R has a three different methods for implementing object oriented programming and we will cover them in th...

11 readings

Graded: Functional and Object-Oriented Programming

FAQs

How It Works

Coursework

Each course is like an interactive textbook, featuring pre-recorded videos, quizzes and projects.

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Connect with thousands of other learners and debate ideas, discuss course material, and get help mastering concepts.

Certificates

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Creators

Johns Hopkins University

The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.

Pricing

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Access to course materials	Available	Available
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Ratings and Reviews

Rated 4.4 out of 5 of 87 ratings

More advanced, challenging course. Still, enjoyable and enlightening. Mentoring on this course is really helpful too!

Awesome interactive Swirl

It is a good course that forced me to understand the s3 and s4 object of R and have gained an appreciation of "methods belonging to functions not belonging to objects".

More information material will be helpful

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