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Autor Tópico: R Programming Masterclass for Data Science and Data Analysis  (Lida 175 vezes)

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R Programming Masterclass for Data Science and Data Analysis
« em: 07 de Outubro de 2019, 14:17 »

R Programming Masterclass for Data Science and Data Analysis
.MP4 | Video: 1280x720, 30 fps(r) | Audio: AAC, 44100 Hz, 2ch | 2.25 GB
Duration: 6.5 hours | Genre: eLearning | Language: English
R Programming for Data Science & Data Analysis, Basic to Advanced in R, Data Visualization with GGDescription2 and dplyr, tidyr.

What you'll learn

    R Programming Basics
    Data Types, Vectors and Matrices in R
    Data Frames and Lists
    Working with Files
    Logical Operators, Statements and Loops
    Functions and Core Concepts in R
    Advanced R Programming
    Apply Function, Regular Expressions
    Math functions, Date and Timestamps
    Data Manipulation and Data Cleaning
    dplyr Package, Pipe Operator and tidyr Package

Requirements

    No Prior Knowledge or Experience Needed, Only a Passion to Learn !

Description

This  is a Comprehensive Course to Learn R Programming for Data science, Data Analysis, Machine Learning and Data Visualization !

With this course you will learn R Programming from Very Beginning to Advanced Level Step by Step

Here we will cover almost every topic that comes under R Programming umbrella

In this course you will learn, ,

1) R Programming Basics : Arithmetic in R, Variables in R, Data Types in R, Vectors in R, Vector Operations, Comparison Operators, Indexing and Slicing in Vectors

2) Matrices in R : Creating A Matrix, Arithmetics in Matrix, Operations in Matrix, Indexing and Selection in Matrix, Factor Function

3) Data Frames : Data Frame Basics, Indexing and Selection in Data Frames, Data Frame Operations

4) Lists in R

5) Working with Files : Working with CSV Files and Excel Files

6) Core Programming Concepts in R : Logical Operators, if, else and else if statements, While loop, For loops, Functions in R

7) Advanced R Programming : Built in Features, Apply Function, Regular Expressions, Math functions, Date and Timestamps

8) Data Manipulation in R : dplyr Package, Pipe Operator, tidyr Package

9) Data Visualization with ggDescription2

In summary, this course has been designed for all skill levels and even if you have no programming or statistical background you will be successful in this course!

Regards,

Vijay Gadhave

Who this course is for:

    Students who want to start a career in the field of Data Science and Machine Learning
    Professionals who want to start a new career in Data Science
    Anyone interested in becoming a Data Scientist
   

               

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