This course is part of the Mastering Software Development in R Specialization

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stars
557 ratings

Roger D. Peng, PhD +1 more instructor

29,436 already enrolled

Offered By

Mastering Software Development in R SpecializationJohns Hopkins University

About this Course

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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.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Course 2 of 5 in the

Mastering Software Development in R Specialization

Intermediate Level

Approx. 18 hours to complete

English

Subtitles: Arabic, French, Portuguese (European), Chinese (Simplified), Italian, Portuguese (Brazilian), Vietnamese, Korean, German, Russian, Indonesian, English, Spanish

Skills you will gain

Logic Programming
R Programming
Object-Oriented Programming (OOP)
Functional Programming

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Course 2 of 5 in the

Mastering Software Development in R Specialization

Intermediate Level

Approx. 18 hours to complete

English

Subtitles: Arabic, French, Portuguese (European), Chinese (Simplified), Italian, Portuguese (Brazilian), Vietnamese, Korean, German, Russian, Indonesian, English, Spanish

Instructors

Instructor rating

3.95/5 (30 Ratings)

Roger D. Peng, PhD

Associate Professor, Biostatistics

Bloomberg School of Public Health

1,451,038 Learners

37 Courses

Brooke Anderson

Assistant Professor, Environmental & Radiological Health Sciences

Colorado State University

70,069 Learners

5 Courses

Offered by

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.

Syllabus - What you will learn from this course

Content Rating92%(3,119 ratings)

Week

Week 1

8 minutes to complete

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 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.

8 minutes to complete

1 video (Total 1 min), 3 readings

2 hours to complete

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.

2 hours to complete

17 readings

2 hours to complete

Functions: Lesson Choices

2 hours to complete

Week

Week 2

3 hours to complete

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 error and exception handling in R for writing robust code.

3 hours to complete

19 readings

3 hours to complete

Functional Programming: Lesson Choices

3 hours to complete

Week

Week 3

2 hours to complete

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 to optimize your code for maximum efficiency.

2 hours to complete

15 readings

Week

Week 4

5 hours to complete

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 this section.

5 hours to complete

11 readings

Reviews

4.3

141 reviews

5 stars
58.96%
4 stars
22.58%
3 stars
10.39%
2 stars
2.86%
1 star
5.19%

TOP REVIEWS FROM ADVANCED R PROGRAMMING

by CISep 25, 2017

This course helped me to figure out what additional skills I need to work on to improve my R coding skills.

by JSOct 30, 2017

The final homework assignment is tough if you are a newcomer to R. It is sink or swim time. Worth it if you can get through it.

by MFFeb 22, 2017

For me the course provided a quick and easy introduction to the 'purr' package as well as clarity on the current state of R's object oriented programming system.

by MKNov 28, 2019

Good course, nothing much to say, definitely teaches the use of R, not quite sure it is "advanced" but I guess...

View all reviews

About the Mastering Software Development in R Specialization

R is a programming language and a free software environment for statistical computing and graphics, widely used by data analysts, data scientists and statisticians. This Specialization covers R software development for building data science tools. As the field of data science evolves, it has become clear that software development skills are essential for producing and scaling useful data science results and products.

This Specialization will give you rigorous training in the R language, including the skills for handling complex data, building R packages, and developing custom data visualizations. You’ll be introduced to indispensable R libraries for data manipulation, like tidyverse, and data visualization and graphics, like ggplot2. You’ll learn modern software development practices to build tools that are highly reusable, modular, and suitable for use in a team-based environment or a community of developers. This Specialization is designed to serve both data analysts, who may want to gain more familiarity with hands-on, fundamental software skills for their everyday work, as well as data mining experts and data scientists, who may want to use R to scale their developing and programming skills, and further their careers as data science experts.

Frequently Asked Questions

When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

More questions? Visit the Learner Help Center.

Advanced R Programming

About this Course

Skills you will gain