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- Welcome to Introduction to R Programming for Data Science
- Introduction to R Language
- Basic Data Types
- Math, Variables, and Strings
- R Environment
- Introduction to RStudio
- Writing and Running R in Jupyter Notebooks
Introduction to R Programming for Data Science
Quick Facts
| particular | details | |||
|---|---|---|---|---|
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Medium of instructions
English
|
Mode of learning
Self study
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Mode of Delivery
Video and Text Based
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Course overview
The Introduction to R Programming for Data Science online certification was developed by IBM Skills Network and instructed by Yan Luo, Ph.D., Data Scientist, and Developer and is made available through Coursera and is targeted at individuals who are interested in learning the fundamental ideas behind data science and data analysis operations using the features of R programming. The Introduction to R Programming for Data Science online course teaches individuals about the fundamentals of the R language, including data types, data manipulation methods, and how to carry out basic programming operations.
Introduction to R Programming for Data Science online classes contains 10 hours of video-based study materials that introduce individuals to basic programming concepts, standard data structures, and data manipulation techniques, all with the assistance of the R programming language. Individuals who successfully finish this program will be able to develop a basic program in RStudio, work with data in a data frame or matrix, and complete the final project as professional data analysts utilizing Watson Studio and Jupyter notebooks to gather and evaluate data-driven insights.
The highlights
- Shareable certificate of completion
- Self-paced course
- 10 hours effort
- 100% online content
- Flexible deadlines
Program offerings
- English video lectures with subtitles
- 100% online content
- Learning resources
- Graded assignments
- Practice quizzes
- Graded quizzes
- Accessible on mobile devices and tv.
Course and certificate fees
Depending upon the number of hours required to complete the learning, the candidates may choose from any of the following Introduction to R Programming for Data Science certification fees mentioned in the table down below. All these structures include certificates after course completion.
Introduction to R Programming for Data Science Fee Details
Description | Amount in INR |
1 Month | Rs. 3,277/month |
| 3 Month | Rs. 2,185/month |
| 6 Month | Rs. 1,639/month |
certificate availability
Yes
certificate providing authority
Coursera
Who it is for
What you will learn
Data science knowledge
R programming
After completing the Introduction to R Programming for Data Science certification course, individuals will be introduced to the basic concepts of R programming for data science activities. Individuals will explore the strategies to manipulate data types using Jupyter Notebooks and RStudio as well as will acquire the knowledge of the techniques to manipulate R data structures including factors, lists, vectors, and data frames. Individuals will learn about concepts associated with web scraping, control flow, regular expressions, and string operations.
The syllabus
Module 1 : R Basics
Videos
Reading
- Summary & Highlights
Practice Exercises
- Practice Quiz
- Graded Quiz
Module 2 : Common Data Structures
Videos
- Vectors and Factors
- Vector Operations
- Lists
- Arrays and Matrices
- Data Frames
Reading
- Summary & Highlights
Practice Exercises
- Practice Quiz
- Graded Quiz
Module 3 : R Programming Fundamentals
Videos
- Conditions and Loops
- Functions in R
- String Operations in R
- Regular Expressions
- Date Format in R
- Debugging
Reading
- Summary & Highlights
Practice Exercises
- Practice Quiz
- Graded Quiz
Module 4 : Working with Data
Videos
- Reading CSV, Excel, and Built-in Datasets
- Reading Text Files in R
- Writing and Saving to Files
- HTTP Request and REST API
- Web Scraping in R
Reading
- Summary & Highlights
Practice Exercises
- Practice Quiz
- Graded Quiz
Module 5 : Final Project
Readings
- Download and Complete the Tasks in a Notebook
- Congratulations & Next Steps
- Credits and Acknowledgments
Instructors
Mr Yan Luo
Data Scientist
IBM
Ph.D
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