R Programming for Data Science and Machine Learning

R Programming for Data Science and Machine Learning, available at $39.99, has an average rating of 4.85, with 25 lectures, 6 quizzes, based on 94 reviews, and has 18309 subscribers.

You will learn about End-to-end knowledge on R programming language Become an R Programmer from scratch R Introduction & Installation R Data Structures R Data Types, R Packages Build a Calculator using R Condition Statements, Looping, Repeat Statements in R Sum of N natural numbers, Sum Recursion Switch Statement, Functions, Factors in R Data Preprocessing and Dataframes in R Data Reshaping R Math built-in Functions Melting and Casting in R This course is ideal for individuals who are Beginners and newbies in Programming (R, Python) or Anyone aspiring for a career as Software Developer / Programmer or R & Python Programmers or Data Scientists – Python/R Programming or Data Analysts and Data Visualization Developers or Technical Consultants or Data Engineers – R, Big Data or R Developers or Application Developers or Software Consultants or Machine Learning Engineers – R, Python or Data Science Engineers or Software Engineers & Developers or Analytics Professionals or Statisticians and Researchers It is particularly useful for Beginners and newbies in Programming (R, Python) or Anyone aspiring for a career as Software Developer / Programmer or R & Python Programmers or Data Scientists – Python/R Programming or Data Analysts and Data Visualization Developers or Technical Consultants or Data Engineers – R, Big Data or R Developers or Application Developers or Software Consultants or Machine Learning Engineers – R, Python or Data Science Engineers or Software Engineers & Developers or Analytics Professionals or Statisticians and Researchers.

Enroll now: R Programming for Data Science and Machine Learning

Summary

Title: R Programming for Data Science and Machine Learning

Price: $39.99

Average Rating: 4.85

Number of Lectures: 25

Number of Quizzes: 6

Number of Published Lectures: 25

Number of Published Quizzes: 6

Number of Curriculum Items: 31

Number of Published Curriculum Objects: 31

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

End-to-end knowledge on R programming language
Become an R Programmer from scratch
R Introduction & Installation
R Data Structures
R Data Types, R Packages
Build a Calculator using R
Condition Statements, Looping, Repeat Statements in R
Sum of N natural numbers, Sum Recursion
Switch Statement, Functions, Factors in R
Data Preprocessing and Dataframes in R
Data Reshaping
R Math built-in Functions
Melting and Casting in R

Who Should Attend

Beginners and newbies in Programming (R, Python)
Anyone aspiring for a career as Software Developer / Programmer
R & Python Programmers
Data Scientists – Python/R Programming
Data Analysts and Data Visualization Developers
Technical Consultants
Data Engineers – R, Big Data
R Developers
Application Developers
Software Consultants
Machine Learning Engineers – R, Python
Data Science Engineers
Software Engineers & Developers
Analytics Professionals
Statisticians and Researchers

Target Audiences

Beginners and newbies in Programming (R, Python)
Anyone aspiring for a career as Software Developer / Programmer
R & Python Programmers
Data Scientists – Python/R Programming
Data Analysts and Data Visualization Developers
Technical Consultants
Data Engineers – R, Big Data
R Developers
Application Developers
Software Consultants
Machine Learning Engineers – R, Python
Data Science Engineers
Software Engineers & Developers
Analytics Professionals
Statisticians and Researchers

A warm welcome to the R Programming for Beginnerscourse by Uplatz.

R is a programming language regularly used for arithmetical computing and graphical demonstration to examine and visualize data. R is a software environment which is used to analyze numerical data and graphical representation. R lets us to do sectional programming using functions. R programming language was named R, founded on the first name letter of the two authors – Robert Gentleman and Ross Ihaka. An overall understanding of R should cover topics such as introduction, features, installation, RStudio ide, variables, datatypes, operators, if statement, vector, data handing, graphics, statistical modelling, etc. R not only allows us to do branching and looping but also allows to do modular programming using functions. R allows integration with the procedures written in the C, C++, .NET, Python, and FORTRAN languages to improve efficiency.

R is one of the most significant instrument which is used by investigators, data analyst, statisticians, and marketers for retrieving, cleaning, analyzing, visualizing, and presenting data. R is available for Linux, MacOS, and Windows. R’s binary and logical operators will look very acquainted to programmers. R can be used to compute a large variety of classical statistic tests. With R, it’s also possible to perform classification analysis such as Principal component analysis and clustering. Many types of graphs can be drawn using R, including, box plot, histogram, density curve, scatter plot, line plot, bar plot, etc.

R Programming for Beginners – Course Syllabus

Introduction to R Language
R Installation
R Data Structures
R Data Types
R Packages
Simple Calculator using R
R as a Calculator
Condition Statements in R
Looping in R
Repeat Statement in R
Sum of N Natural Numbers
Sum Recursion
Switch Statement in R
Data Pre-processing
Functions in R
Factors in R
Data frames in R
Data Reshaping
R Math built-in Functions
Melting and Casting in R

Course Curriculum

Chapter 1: Introduction to R Language

Lecture 1: Introduction to R Language

Chapter 2: R Installation

Lecture 1: R Installation

Chapter 3: R Data Structures

Lecture 1: R Data Structures

Chapter 4: R Data Types

Lecture 1: R Data Types – part 1

Lecture 2: R Data Types – part 2

Chapter 5: R Packages

Lecture 1: R Packages

Chapter 6: Simple Calculator using R

Lecture 1: Simple Calculator using R

Chapter 7: R as a Calculator

Lecture 1: R as a Calculator

Chapter 8: Condition Statements in R

Lecture 1: Condition Statements in R – part 1

Lecture 2: Condition Statements in R – part 2

Chapter 9: Looping in R

Lecture 1: Looping in R

Chapter 10: Repeat Statement in R

Lecture 1: Repeat Statement in R

Chapter 11: Sum of N Natural Numbers

Lecture 1: Sum of N Natural Numbers

Chapter 12: Sum Recursion

Lecture 1: Sum Recursion

Chapter 13: Switch Statement in R

Lecture 1: Switch Statement in R

Chapter 14: Data Pre-processing

Lecture 1: Data Pre-processing

Chapter 15: Functions in R

Lecture 1: Functions in R

Chapter 16: Factors in R

Lecture 1: Factors in R

Chapter 17: Data Frames in R

Lecture 1: Data Frames in R

Lecture 2: Merging Data Frame in R

Chapter 18: Data Reshaping

Lecture 1: Data Reshaping – part 1

Lecture 2: Data Reshaping – part 2

Lecture 3: Data Reshaping – part 3

Chapter 19: R Math built-in Functions

Lecture 1: R Math built-in Functions

Chapter 20: Melting and Casting in R

Lecture 1: Melting and Casting in R

Chapter 21: End of Course Quiz

Chapter 22: Coding Exercises

Instructors

Uplatz Training
Fastest growing global Technology & Cloud Training Provider

Rating Distribution

1 stars: 2 votes
2 stars: 5 votes
3 stars: 13 votes
4 stars: 29 votes
5 stars: 45 votes

Frequently Asked Questions

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You can view and review the lecture materials indefinitely, like an on-demand channel.

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