Data Science and Machine Learning Bootcamp with R

BY
Udemy

Mode

Online

Fees

₹ 4099

Quick Facts

particular details
Medium of instructions English
Mode of learning Self study
Mode of Delivery Video and Text Based

Course and certificate fees

Fees information
₹ 4,099
certificate availability

Yes

certificate providing authority

Udemy

The syllabus

Course Introduction

  • Introduction to Course
  • Course Curriculum
  • What is Data Science?
  • Course FAQ

Course Best Practices

  • How to Get Help in the Course!
  • Welcome to the Course.
  • Installation and Set-Up

Windows Installation Setup

  • Windows Installation Procedure

Mac OS Installation Setup

  • Mac OS Installation Procedure

Linux Installation

  • Linux/Unbuntu Installation Procedure

Development Environment Overview

  • Development Environment Overview
  • Course Notes
  • Guide to RStudio

Introduction to R Basics

  • Introduction to R Basics
  • Arithmetic in R
  • Variables
  • R Basic Data Types
  • Vector Basics
  • Vector Operations
  • Comparison Operators
  • Vector Indexing and Slicing
  • Getting Help with R and RStudio
  • R Basics Training Exercise
  • R Basics Training Exercise - Solutions Walkthrough

R Matrices

  • Introduction to R Matrices
  • Creating a Matrix
  • Matrix Arithmetic
  • Matrix Operations
  • Matrix Selection and Indexing
  • Factor and Categorical Matrices
  • Matrix Training Exercise
  • Matrix Training Exercises - Solutions Walkthrough

R Data Frames

  • Introduction to R Data Frames
  • Data Frame Basics
  • Data Frame Indexing and Selection
  • Overview of Data Frame Operations - Part 1
  • Overview of Data Frame Operations - Part 2
  • Data Frame Training Exercise
  • Data Frame Training Exercises - Solutions Walkthrough

R Lists

  • List Basics

Data Input and Output with R

  • Introduction to Data Input and Output with R
  • CSV Files with R
  • Note on R with Excel Download
  • Excel Files with R
  • SQL with R
  • Web Scraping with R

R Programming Basics

  • Introduction to Programming Basics
  • Logical Operators
  • if, else, and else if Statements
  • Conditional Statements Training Exercise
  • Conditional Statements Training Exercise - Solutions Walkthrough
  • While Loops
  • For Loops
  • Functions
  • Functions Training Exercise
  • Functions Training Exercise - Solutions

Advanced R Programming

  • Introduction to Advanced R Programming
  • Built-in R Features
  • Apply
  • Math Functions with R
  • Regular Expressions
  • Dates and Timestamps

Data Manipulation with R

  • Data Manipulation Overview
  • Guide to Using Dplyr
  • Guide to Using Dplyr - Part 2
  • Pipe Operator
  • Quick note on Dpylr exercise
  • Dplyr Training Exercise
  • Dplyr Training Exercise - Solutions Walkthrough
  • Guide to Using Tidyr

Data Visualization with R

  • Overview of ggplot2
  • Histograms
  • Scatterplots
  • Barplots
  • Boxplots
  • 2 Variable Plotting
  • Coordinates and Faceting
  • Themes
  • ggplot2 Exercises
  • ggplot2 Exercise Solutions

Data Visualization Project

  • Data Visualization Project
  • Data Visualization Project - Solutions Walkthrough - Part 1
  • Data Visualization Project Solutions Walkthrough - Part 2

Interactive Visualizations with Plotty

  • Overview of Plotly and Interactive Visualizations
  • Resources for Plotly and ggplot2

Capstone Data Project

  • Introduction to Capstone Project
  • Capstone Project Solutions Walkthrough

Introduction to Machine Learning with R

  • ISLR PDF
  • Introduction to Machine Learning

Machine Learning with R - Linear Regression

  • Introduction to Linear Regression
  • Linear Regression with R - Part 1
  • Linear Regression with R - Part 2
  • Linear Regression with R - Part 3

Machine Learning Project - Linear Regression

  • Introduction to Linear Regression Project
  • ML - Linear Regression Project - Solutions Part 1
  • ML - Linear Regression Project - Solutions Part 2

Machine Learning with R - Logistic Regression

  • Introduction to Logistic Regression
  • Logistic Regression with R - Part 1
  • Logistic Regression with R - Part 2

Machine Learning Project - Logistic Regression

  • Introduction to Logistic Regression Project
  • Logistic Regression Project Solutions - Part 1
  • Logistic Regression Project Solutions - Part 2
  • Logistic Regression Project - Solutions Part 3

Machine Learning with R - K Nearest Neighbors

  • Introduction to K Nearest Neighbors
  • K Nearest Neighbors with R

Machine Learning Project - K Nearest Neighbors

  • Introduction K Nearest Neighbors Project
  • K Nearest Neighbors Project Solutions

Machine Learning with R - Decision Trees and Random Forests

  • Introduction to Tree Methods
  • Decision Trees and Random Forests with R

Machine Learning Project - Decision Trees and Random Forests

  • Introduction to Decision Trees and Random Forests Project
  • Tree Methods Project Solutions - Part 1
  • Tree Methods Project Solutions - Part 2

Machine Learning with R - Support Vector Machines

  • Introduction to Support Vector Machines
  • Support Vector Machines with R

Machine Learning Project - Support Vector Machines

  • Introduction to SVM Project
  • Support Vector Machines Project - Solutions Part 1
  • Support Vector Machines Project - Solutions Part 2

Machine Learning with R - K-Means Clustering

  • Introduction to K-Means Clustering
  • K Means Clustering with R

Machine Learning Project - K-Means Clustering

  • Introduction to K Means Clustering Project
  • K Means Clustering Project - Solutions Walkthrough

Machine Learning with R - Natural Language Processing

  • Introduction to Natural Language Processing
  • Natural Language Processing with R - Part 1
  • Natural Language Processing with R - Part 2

Machine Learning with R - Neural Nets

  • Introduction to Neural Nets
  • Neural Nets with R

Machine Learning Project - Neural Nets

  • Introduction to Neural Nets Project
  • Neural Nets Project - Solutions

Bonus Section

  • Bonus Lecture

Instructors

Mr Jose Portilla
Head of Data Science
Udemy

Other Bachelors, M.S

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