Data Science: R Programming Complete Diploma

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Learn all the R skills you need to become a Professional and Certified R Programmer with this Complete Bootcamp

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

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Description

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

# Data Science: R Programming Complete Diploma 2023

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

In this course, Iā€™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.


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This course will cover all 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 factorsAnd 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

English
language

Content

Module 0: Introduction

Introduction
Downloading and Installing R
Downloading and Installing the RStudio IDE
Setup working directory

Module 1: Variables, Data Types and Hints

Variables in detail 1
Variables in detail 2
Variables in detail 3
Variables in detail 4
Data types 1
Data types 2
Data types 3
Code hints

Module 2: Numbers and Math

Type of numbers
Type conversion
Math operations

Module 3: Characters

Strings 1
Strings 2
Strings 3
Strings 4
Strings 5
Strings 6
Strings 7

Module 4: Logical and operators

Logical values 1
Logical values 2
Operators 1
Operators 2
Operators 3
Operators 4
Operators 5

Module 5: DS – Vectors

DS -Vectors 1
DS -Vectors 2
DS -Vectors 3
DS -Vectors 4
DS -Vectors 5
DS -Vectors 6
DS -Vectors 7

Module 6: DS – Lists

DS – Lists 1
DS – Lists 2
DS – Lists 3
DS – Lists 4

Module 7: DS – Matrices

DS – Matrices 1
DS – Matrices 2
DS – Matrices 3
DS – Matrices 4
DS – Matrices 5

Module 8: DS – Arrays

DS – Arrays 1
DS – Arrays 2
DS – Arrays 3
DS – Arrays 4
DS – Arrays 5

Module 9: DS – Data Frame

DS – Data Frame 1
DS – Data Frame 2
DS – Data Frame 3
DS – Data Frame 4
DS – Data Frame 5
DS – Data Frame 6

Module 10: DS – Factors

DS – Factors 1
DS – Factors 2
DS – Factors 3
DS – Factors 4

Module 11: Decision making

Conditional statements 1
Conditional statements 2
Conditional statements 3
Conditional statements 4

Module 12: Repetition

While loop 1
While loop 2
While loop 3
For loop 1
For loop 2
For loop 3
For loop 4

Module 13: Functional Programming

Functions 1
Functions 2
Functions 3
Functions 4
Functions 5

Module 14: Statistics and Data analysis

Statistics 1
Statistics 2
Statistics 3
Statistics 4
Statistics 5

Module 15: Data Visualization and Graphics

Plotting in R 1
Plotting in R 2
Plotting in R 3
Plotting in R 4
Lines 1
Lines 2
Lines 3
Pie Charts 1
Pie Charts 2
Pie Charts 3
Bars and Histograms 1
Bars and Histograms 2
Bars and Histograms 3
Bars and Histograms 4
Bars and Histograms 5
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