Get updates on Eligibility, Admission, Placements Fees Structure
Quick Facts
| Medium Of Instructions | Mode Of Learning | Mode Of Delivery |
|---|---|---|
| English | Self Study | Video and Text Based |
Course Overview
The Advanced R Programming certification course is the second one in the ‘Mastering Software Development in R Specialization’ series offered by Coursera. The course curriculum explores the advanced topics such as functional programming in R, object-oriented programming, robust error handling, profiling and benchmarking, debugging, as well as the proper design of functions.
The Coursera Advanced R Programming online course, offered in collaboration with Johns Hopkins University, aims to prepare students for unique data challenges and to identify everyday data analysis tasks. They will also learn how to define new data types in R, create functionalities specific to these for enabling cleaner execution of tasks related to data science, and stronger reusability within a team. All this is taught through pre-recorded videos, readings, graded quizzes, and assignments, for a valuable learning experience.
Furthermore, the Coursera Advanced R Programming online course is designed, keeping in mind the convenience of students. Hence, the modules are self-paced and entirely online to help students learn from the comfort of their own space. Upon satisfactory completion, participants get a \shareable certificate.
The Highlights
- 100% Online
- Flexible deadlines
- Shareable Certificate
- Self-Paced course
- Intermediate level
- Subtitles in Chinese (Simplified) and English
- Graded programming assignments
- Completion in approximately 18 hours
Programme Offerings
- Shareable Certificate
- online learning
- Graded Assignments
- Flexible Deadlines
- peer feedback
Courses and Certificate Fees
| Certificate Availability | Certificate Providing Authority |
|---|---|
| yes | Johns HopkinsCoursera |
Advanced R Programming Fee Structure :
Fees components | Amount |
Advanced R Programming (audit only) | Free |
| Advanced R Programming | Rs. 1,676 /- |
| Advanced R Programming | Rs. 3,369 /- |
| Advanced R Programming | Rs. 5,029 /- |
Eligibility Criteria
As the Advanced R Programming online training is a programming course, some prior experience in any programming language is recommended for the students. Working knowledge of mathematics up to Algebra (neither Linear Algebra or Calculus are required) is also necessary for the understanding of the course.
What you will learn
On completing the Coursera Advanced R Programming course, students will have:
- Strong programming skills in the R language and an understanding of the technicalities of the language.
- Identify and solve unique problems and tasks that come up regularly in a data science environment.
- In-depth understanding of R language and familiarity with the underlying structures and new data types.
- Better career prospects and fundamental software skills in the field of data science.
- Skills in R Programming, Functional Programming, Object-Oriented Programming (OOP), and Logic Programming.
Who it is for
The Coursera Advanced R Programming online course is designed to serve data analysts, data mining experts, and data scientists. The programme will facilitate such individuals who want to use the R language to scale their overall programming skills, developing skills, and further their career prospects as data science experts.
Admission Details
To apply to the Advanced R Programming online course by Coursera:
- Visit the Course page.
- Find ‘Advanced R Programming course’ on the website.
- Click on the ‘Enroll for FREE’ option.
- You will get a dialogue box, where you need to Signup.
- Those already having an account can log in and proceed.
Application Details
The Coursera Advanced R Programming course does not have any admission form per se. To join the programme, sign up on the website using Email ID and password. After signing up, choose a suitable enrolment option and proceed with the certification course.
The Syllabus
Video
- Welcome to Advanced R Programming
Readings
- Syllabus
- Course Textbook: Mastering Software Development in R
- swirl Assignments
Readings
- Control Structures Overview
- if-else
- for Loops
- Nested for loops
- next, break
- Summary
- Functions Overview
- Code
- Function interface
- Default values
- Re-factoring code
- Dependency Checking
- Vectorization
- Argument Checking
- R package
- When Should I Write a Function?
- Summary
Assignment
- Swirl Lesson
Programming Assignment
- Swirl Lesson
Readings
- What is Functional Programming?
- Core Functional Programming Functions
- Map
- Reduce
- Search
- Filter
- Compose
- Partial Application
- Side Effects
- Recursion
- Summary
- Expressions
- Environments
- Execution Environments
- What is an error?
- Generating Errors
- When to generate errors or warnings
- How should errors be handled?
- Summary
Assignment
- Swirl Lesson
Programming Assignment
- Swirl Lesson
Readings
- Debugging Overview
- traceback()
- Browsing a Function Environment
- Tracing Functions
- Using debug() and debugonce()
- recover()
- Final Thoughts on Debugging
- Summary
- Profiling Overview
- microbenchmark
- profvis
- Find out more
- Summary
- Non-standard evaluation
- Summary
Assignment
- Debugging and Profiling
Readings
- OOP Overview
- Object Oriented Principles
- S3
- S4
- Reference Classes
- Summary
- Overview
- Reuse existing data structures
- Compose simple functions with the pipe
- Embrace functional programming
- Design for humans
Peer Review
- Functional and Object-Oriented Programming