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
We are witnessing and adapting to the fourth industrial revolution, Industry 4.0, powered by Big Data and AI. At the global level, data integration has become highly essential for organisations and businesses to achieve global competitiveness. With the prevalence of Big Data all around, it becomes highly relevant to explore the underlying information and reap optimum rewards. In this scenario, data science and analytics enable decision-makers and business leaders to understand, manage and utilise data effectively.
R is a free, open-source programming language that is widely used by data scientists and analysts for developing software and applications in a data science setting. R offers tools and techniques for data analysis, statistical computations and data visualisation. R is available to use on various operating systems and is widely recognised for its extensibility, which allows developers to develop and distribute their own software as add-on packages. These features make R programming an ideal choice for data science experts and data analysts to utilise R in a variety of fields and areas.
The R Programming Environment online certificate course offered by Johns Hopkins University via the Coursera platform aims at providing useful knowledge of R Programming Language to data scientists, data analysts and data science experts to efficiently work in data science settings. This 100% online programme is of intermediate level and the first course in the Mastering Software Development in R specialisation.
The Highlights
- Offered by Johns Hopkins University through Coursera
- Learning through 100% online mode
- Approximately 27 hours of videos and readings
- Flexible learning and deadline scheduling
- Interaction with top instructors
- The option of 7-day Free Trial and Financial Aid
- English, Portuguese, Russian, Spanish and French subtitles
- Shareable certificate for online profile/CV
Programme Offerings
- Reading
- videos
- Practice Exercises
- quizzes
Courses and Certificate Fees
| Certificate Availability | Certificate Providing Authority |
|---|---|
| yes | Johns HopkinsCoursera |
The R Programming Environment Fees Structure :
Fees components | Fees |
| The R Programming Environment (audit only) | Free |
| The R Programming Environment - 1 month | Rs. 1,676 /- |
| The R Programming Environment - 3 months | Rs. 3,369 /- |
| The R Programming Environment - 6 months | Rs. 5,029 /- |
Eligibility Criteria
Certification Qualifying Details
To qualify for certification, participants of this certificate course are required to complete the course work including passing all the graded assignments. Such assignments can be in the form of quizzes or other programming assignments as applicable.
What you will learn
Upon completion of this certification programme, participants will be able to:
- Read data in R and understand the basics of R.
- Display skills in managing complex data, developing data visualisations and build R packages.
- Manipulate data using tidyverse and ggplot2.
- Get exposure to new practices in software development.
- Efficiently deal with regular and text expressions using R packages and tools.
- Diagnose problems and find solutions while dealing with large datasets.
- Use broad range of data sources to create tidy datasets.
Who it is for
The R Programming Environment online certification course is designed for:
- Data analysts aspiring to master basic software skills in their regular work.
- Data mining experts wanting to scale programming and developing skills using R.
- Data scientists seeking to advance in their career as data science experts.
- Professionals and individuals working in data science team or developers’ community.
Admission Details
To enroll in The R Programming Environment online certificate programme, the participants are required to follow the below-mentioned steps.
Step 1: Visit the course page. https://www.coursera.org/learn/r-programming-environment
Step 2: Click on “Enroll for Free”.
Step 3: Use your Google or Email credentials to log in or sign up.
Step 4: Choose between “5-Course Specialisation” or “Coursera Plus” options.
Step 5: By clicking on “5-Course Specialisation”, candidates will get access to course content (videos) and graded assignments (quizzes) in the Mastering Software Development in R Specialisation, including the R Programming Environment course. Applicants will be eligible for a 7-day free trial for the course, after which, the monthly charges will be applicable.
Step 6: In the Coursera Plus option, applicants will get access to more than 3000 courses, including the R Programming Environment course. In this option too, applicants will be eligible for a 7-day free trial, after which, monthly charges of the Coursera Plus plan will be applicable. Other benefits of Coursera Plus will include:
- Guided projects
- Varied specialisations
- Flexibility in learning
- Less spending on taking multiple courses
- Unlimited professional certificates
Step 7: By clicking on the ‘Audit the single course’ link, applicants will be able to browse through the whole course, barring the graded assignments.
Step 8: Select the option of your choice and start the 7-day free trial or audit the course.
The Syllabus
Video
- Welcome to the R Programming Environment
Readings
- Course Textbook: Mastering Software Development in R
- Syllabus
- Swirl Assignments
- Datasets
- Lesson Introduction
- Evaluation
- Objects
- Numbers
- Creating Vectors
- Mixing Objects
- Explicit Coercion
- Matrices
- Lists
- Factors
- Missing Values
- Data Frames
- Names
- Attributes
- Summary
- The Importance of Tidy Data
- The “Tidyverse”
- Reading Tabular Data with the readr Package
- Reading Web-Based Data
- Flat files online
- Requesting data through a web API
- Scraping web data
- Parsing JSON, XML, or HTML data
Assignment
- Swirl Lessons
Programming Assignment
- Swirl Lessons
Readings
- Basic Data Manipulation
- Piping
- Summarizing data
- Selecting and filtering data
- Adding, changing, or renaming columns
- Spreading and gathering data
- Merging datasets
- Working with Dates, Times, Time Zones
- Converting to a date or date-time class
- Pulling out date and time elements
- Working with time zones
Assignment
- Swirl Lessons
Readings
- Text Processing and Regular Expressions
- Text Manipulation Functions in R
- Regular Expressions
- RegEx Functions in R
- The stringr Package
- Summary
- The Role of Physical Memory
- Back of the Envelope Calculations
- Internal Memory Management in R
Assignment
- Swirl Lessons
Readings
- Working with Large Datasets
- In-memory strategies
- Out-of-memory strategies
- Diagnosing Problems
- How to Google Your Way Out of a Jam
- Asking for Help
- Quiz Instructions
Assignment
- Reading and Summarizing Data
Evaluation process
Participants need to complete assignments such as quizzes and other programming assignments that are included in the course to get the course certificate of completion from Coursera. The course has flexible deadlines, which enables participants to save their progress. Participants will get a shareable Certificate from Coursera only after completing and passing all the required graded assignments.