R basics for Data Science , AI , Data Analytics : Part 1

Name: R basics for Data Science , AI , Data Analytics : Part 1
Rating: 4.4 (57 reviews)

Use R for Data Analytics and Data science

Created byShan Singh | 300,000+ Students | Best-Selling Instructor

Last updated 12/2024

English

English [Auto],

What you'll learn

Learn the core principles of programming
Learn how to create variables
Learn how to use functions
Learn how to use various data structures in R

Course content

4 sections • 16 lectures • 1h 51m total length

keywords In R3:02
Explore the basics of R with a focus on keywords, reserved words, and how to view them using the R help topic, applying a practical notebook workflow.
Identifiers in R4:47
Identify how R identifiers name variables, functions, or objects. Learn the naming rules: letters, numbers, dot and underscore are allowed with restrictions on starting characters and symbol use.
Comments in R5:03
Learn how to annotate and explain your R code with comments, using single line and multi-line hashes to improve readability, illustrated by an area of a circle example.
Statements in R4:32
Learn how expressions in R form statements, and distinguish single line from multi line statements to improve readability while summing numbers and printing results using variables like total_sum.
What are variables in R & its use6:28
Learn how variables in R represent changing values over time, how to store and retrieve them via symbol tables, memory allocation, and linking variables to memory addresses.
Types of Variable assignment in R4:43
Learn four ways to assign variables in R—equals operator, leftward and rightward assignment, and the assign function—understanding when each method is used and how they store values.

Data types In R11:01
Explore the core data types in R—numeric, integer, complex, character, and logical—and how decimals and text are stored and inspected with class and as.integer.
Operators In R9:33
Learn to use arithmetic, comparison, and logical operators in R, including addition, subtraction, multiplication, division, and modulo. Explore the concatenation operator c and the membership operator %in% with practical examples.

Conditional Statements in R9:02
Learn how to use conditional statements in R, including if, if else, and else if, with practical examples and step-by-step logic.
Loops & Indentation in R9:18
Explore loops and indentation in R, using for and while loops to print a statement multiple times, explain loop syntax, and emphasize readable indentation practices.
what are Functions in R ?8:20
Explore how functions in R encapsulate repeatable tasks, create custom median and summation functions, use inbuilt mean, and understand vectors, arguments, and the return statement.

What are Vector in R ?7:47
Discover vectors in R, one-dimensional data structures that store the same data type; learn to create vectors with c, compute means, and the coerce function converts values when mixing types.
Basic operation on Vector5:44
Master basic vector operations in R, including indexing, slicing, and appending values with the append function.
What are list in R ?9:03
Explore lists in R as a heterogeneous collection that stores multiple data types, using named elements to create key-value pairs similar to dictionaries.
Basic operation on List6:08
Explore basic list operations in R, including accessing elements, inserting values, and appending city keys with corresponding values using single brackets, double brackets, and the dollar operator.
Dataframe in R !7:07
Learn how the R data frame, a two dimensional extension of a list, uses columns and rows, created with data.frame and accessed via dollar, single bracket, or double bracket.

Requirements

No prior knowledge or experience needed. Only a passion to be successful!

Description

Are you interested in data science?

Do you want to learn R totally from scratch?

Are you looking for an easy step by step approach to get into R?

Do you want to take an easy R course for BEGINNERS?

Well, if your answer is YES to some of these questions, look no further, this course will help you.

In this free course , will start with installation of R and Jupyter Notebook , then we will learn basics of R like keywords , Identifiers , data types , operators , loops etc.. & data structures in R as well !

This course is truly step-by-step. In every new tutorial we build on what had already learned and move one extra step forward.

The Entire R course is divided into 2 parts ( 2 hours each ) ! You will also get the code I am using for the demos.

What you will learn:

Learn how to use Jupyter Notebook
Learn the core principles of programming
Learn how to create vectors in R
Learn how to create variables
Learn about integer, double, logical, character, and other types in R
Learn how to create a while() loop and a for() loop in R
Learn how to define own functions in R
Learn the various data-structures in R

What R you waiting for?

Who this course is for:

This course is for you if you want to learn how to program in R
This course is for you if you are tired of R courses that are too complicated
This course is for you if you want to learn R by doing

R basics for Data Science , AI , Data Analytics : Part 1

What you'll learn

Explore related topics

Course content

Introduction to R Basics6 lectures • 29min

Data Types and Operators !2 lectures • 21min

Control Structures & Functions in R !3 lectures • 27min

Basic Data Structures in R5 lectures • 36min

Requirements

Description

Who this course is for: