Data Science- R Programming Complete Diploma

Data Science: R Programming Complete Diploma, available at $59.99, has an average rating of 4.44, with 96 lectures, based on 1034 reviews, and has 113299 subscribers.

You will learn about The R working tools and environment for professionals The R syntax and how to explain and describe the code using comments Variables, Values and assignments All the Data types available in R Performing mathematical operations, type conversion built-in functions and many useful built-in functions for math operations Working with collection of characters and strings in R, also essential character operations Logical values and booleans Handling different operations on variables and values by using different types of operators All the Data Structures in R such as vectors, lists, matrices, data frames and factors. And also all the essential operations for these data structures Decision making by using conditional statements in R Repeat block of code and iterate over collections with loops Functional programming and code reusing Statistics and data analysis concepts: datasets, many built-in functions, techniques and tools for statistical operations Data visualizations and Graphics in R: drawing points, line plotting, pie charts, bar charts, histograms and more Get the instructor QA Support This course is ideal for individuals who are Beginner R Programmers or New developers and Engineers or Programming and software development engineering newbies or Developers and Engineers who know other programming language but are new to R or Developers curious about Learning R for data science or Beginner Data Engineers/Scientists It is particularly useful for Beginner R Programmers or New developers and Engineers or Programming and software development engineering newbies or Developers and Engineers who know other programming language but are new to R or Developers curious about Learning R for data science or Beginner Data Engineers/Scientists.

Enroll now: Data Science: R Programming Complete Diploma

Summary

Title: Data Science: R Programming Complete Diploma

Price: $59.99

Average Rating: 4.44

Number of Lectures: 96

Number of Published Lectures: 96

Number of Curriculum Items: 96

Number of Published Curriculum Objects: 96

Original Price: $129.99

Quality Status: approved

Status: Live

What You Will Learn

The R working tools and environment for professionals

The R syntax and how to explain and describe the code using comments

Variables, Values and assignments

All the Data types available in R

Performing mathematical operations, type conversion built-in functions and many useful built-in functions for math operations

Working with collection of characters and strings in R, also essential character operations

Logical values and booleans

Handling different operations on variables and values by using different types of operators

All the Data Structures in R such as vectors, lists, matrices, data frames and factors. And also all the essential operations for these data structures

Decision making by using conditional statements in R

Repeat block of code and iterate over collections with loops

Functional programming and code reusing

Statistics and data analysis concepts: datasets, many built-in functions, techniques and tools for statistical operations

Data visualizations and Graphics in R: drawing points, line plotting, pie charts, bar charts, histograms and more

Get the instructor QA Support

Who Should Attend

Beginner R Programmers

New developers and Engineers

Programming and software development engineering newbies

Developers and Engineers who know other programming language but are new to R

Developers curious about Learning R for data science

Beginner Data Engineers/Scientists

Target Audiences

Beginner R Programmers

New developers and Engineers

Programming and software development engineering newbies

Developers and Engineers who know other programming language but are new to R

Developers curious about Learning R for data science

Beginner Data Engineers/Scientists

Hello and welcome to the exciting world of the R programming language.

#Data Science: R Programming Complete Diploma

Ris one of the most powerful programming languages, for statistical computing and graphical presentation to analyze and visualize data.

In this course, I’m going to show you how to code with R from the R basics to the R advanced concepts.

Also, you will explore how the R programming language can be used today for data analysis and the production of beautiful data visualizations and graphics.

The best part? Every single topic and tool in this course will be explained theoretically and practically with real examples step by step.

This course will coverall the R essentials needed for everyone such as:

The R working tools and environment for professionals

The R syntax and how to explain and describe the code using comments

Variables, Values and assignments

All the Data types available in R.

Performing mathematical operations, type conversion built-in functions and many useful built-in functions for math operations.

Working with collection of characters and strings in R, also essential character operations

Logical values and Booleans.

Handling different operations on variables and values by using different types of operators.

All the Data Structures in R such as vectors, lists, matrices, data frames and factors

And also all the essential operations for these data structures.

decision making by using conditional statements in R.

Repeat block of code and iterate over collections with loops.

Functional programming and code reusing.

Statistics and data analysis concepts: datasets, many built-in functions, techniques and tools for statistical operations.

Graphics and data visualizations in R: drawing points, line plotting, pie charts, bar charts, histograms and more.

You will learn and understand all these concepts and more.

R is free open source, and very widely used by professional statisticians and data scientists.

It is also very popular in certain application areas, including bioinformatics. R is a dynamically typed interpreted language, and is typically used interactively. It has many built-in functions and libraries, and is extensible, allowing users to define their own functions and procedures using R, C or Fortran. It also has a simple object system. So, it’s really powerful!

So, what are you waiting for, enroll now to go through a complete bootcamp of one of the most popular and powerful programming languages on the market for , R.

Become A Professional R Programmer and Data Scientist in no time!

Let’s get started

Course Curriculum

Chapter 1: Module 0: Introduction

Lecture 1: Introduction

Lecture 2: Downloading and Installing R

Lecture 3: Downloading and Installing the RStudio IDE

Lecture 4: Setup working directory

Chapter 2: Module 1: Variables, Data Types and Hints

Lecture 1: Variables in detail 1

Lecture 2: Variables in detail 2

Lecture 3: Variables in detail 3

Lecture 4: Variables in detail 4

Lecture 5: Data types 1

Lecture 6: Data types 2

Lecture 7: Data types 3

Lecture 8: Code hints

Chapter 3: Module 2: Numbers and Math

Lecture 1: Type of numbers

Lecture 2: Type conversion

Lecture 3: Math operations

Chapter 4: Module 3: Characters

Lecture 1: Strings 1

Lecture 2: Strings 2

Lecture 3: Strings 3

Lecture 4: Strings 4

Lecture 5: Strings 5

Lecture 6: Strings 6

Lecture 7: Strings 7

Chapter 5: Module 4: Logical and operators

Lecture 1: Logical values 1

Lecture 2: Logical values 2

Lecture 3: Operators 1

Lecture 4: Operators 2

Lecture 5: Operators 3

Lecture 6: Operators 4

Lecture 7: Operators 5

Chapter 6: Module 5: DS – Vectors

Lecture 1: DS -Vectors 1

Lecture 2: DS -Vectors 2

Lecture 3: DS -Vectors 3

Lecture 4: DS -Vectors 4

Lecture 5: DS -Vectors 5

Lecture 6: DS -Vectors 6

Lecture 7: DS -Vectors 7

Chapter 7: Module 6: DS – Lists

Lecture 1: DS – Lists 1

Lecture 2: DS – Lists 2

Lecture 3: DS – Lists 3

Lecture 4: DS – Lists 4

Chapter 8: Module 7: DS – Matrices

Lecture 1: DS – Matrices 1

Lecture 2: DS – Matrices 2

Lecture 3: DS – Matrices 3

Lecture 4: DS – Matrices 4

Lecture 5: DS – Matrices 5

Chapter 9: Module 8: DS – Arrays

Lecture 1: DS – Arrays 1

Lecture 2: DS – Arrays 2

Lecture 3: DS – Arrays 3

Lecture 4: DS – Arrays 4

Lecture 5: DS – Arrays 5

Chapter 10: Module 9: DS – Data Frame

Lecture 1: DS – Data Frame 1

Lecture 2: DS – Data Frame 2

Lecture 3: DS – Data Frame 3

Lecture 4: DS – Data Frame 4

Lecture 5: DS – Data Frame 5

Lecture 6: DS – Data Frame 6

Chapter 11: Module 10: DS – Factors

Lecture 1: DS – Factors 1

Lecture 2: DS – Factors 2

Lecture 3: DS – Factors 3

Lecture 4: DS – Factors 4

Chapter 12: Module 11: Decision making

Lecture 1: Conditional statements 1

Lecture 2: Conditional statements 2

Lecture 3: Conditional statements 3

Lecture 4: Conditional statements 4

Chapter 13: Module 12: Repetition

Lecture 1: While loop 1

Lecture 2: While loop 2

Lecture 3: While loop 3

Lecture 4: For loop 1

Lecture 5: For loop 2

Lecture 6: For loop 3

Lecture 7: For loop 4

Chapter 14: Module 13: Functional Programming

Lecture 1: Functions 1

Lecture 2: Functions 2

Lecture 3: Functions 3

Lecture 4: Functions 4

Lecture 5: Functions 5

Chapter 15: Module 14: Statistics and Data analysis

Lecture 1: Statistics 1

Lecture 2: Statistics 2

Lecture 3: Statistics 3

Lecture 4: Statistics 4

Lecture 5: Statistics 5

Chapter 16: Module 15: Data Visualization and Graphics

Lecture 1: Plotting in R 1

Lecture 2: Plotting in R 2

Lecture 3: Plotting in R 3

Instructors

SDE Arts by Ahmed EL Mohandes
Where Skills Soar and Careers Take Flight

Ahmed El Mohandes
Expert Software Engineer | Sr. Data Science & ML Consultant

Rating Distribution

1 stars: 9 votes

2 stars: 23 votes

3 stars: 136 votes

4 stars: 395 votes

5 stars: 472 votes

Frequently Asked Questions

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

Can I take my courses with me wherever I go?

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