Data Science and Machine Learning Bootcamp with R
4.8 /5- Offered byUDEMY
Data Science and Machine Learning Bootcamp with R at UDEMY Overview
Duration | 18 hours |
Total fee | ₹599 |
Mode of learning | Online |
Difficulty level | Intermediate |
Official Website | Go to Website  |
Credential | Certificate |
Data Science and Machine Learning Bootcamp with R at UDEMY Highlights
- Compatible on Mobile and TV
- Earn a Cerificate on successful completion
- Get Full Lifetime Access
- Course Instructor
- Jose Portilla
Data Science and Machine Learning Bootcamp with R at UDEMY Course details
- Anyone interested in becoming a Data Scientist
- Program in R
- Use R for Data Analysis
- Create Data Visualizations
- Use R to handle csv,excel,SQL files or web scraping
- Use R to manipulate data easily
- Use R for Machine Learning Algorithms
- Use R for Data Science
- Data Scientist has been ranked the number one job on Glassdoor and the average salary of a data scientist is over $120,000 in the United States according to Indeed! Data Science is a rewarding career that allows you to solve some of the world's most interesting problems! This course is designed for both complete beginners with no programming experience or experienced developers looking to make the jump to Data Science! This comprehensive course is comparable to other Data Science bootcamps that usually cost thousands of dollars, but now you can learn all that information at a fraction of the cost! With over 100 HD video lectures and detailed code notebooks for every lecture this is one of the most comprehensive course for data science and machine learning on Udemy! We'll teach you how to program with R, how to create amazing data visualizations, and how to use Machine Learning with R! Here a just a few of the topics we will be learning: Programming with RAdvanced R FeaturesUsing R Data Frames to solve complex tasksUse R to handle Excel FilesWeb scraping with RConnect R to SQLUse ggplot2 for data visualizationsUse plotly for interactive visualizationsMachine Learning with R, including:Linear RegressionK Nearest NeighborsK Means ClusteringDecision TreesRandom ForestsData Mining TwitterNeural Nets and Deep LearningSupport Vectore Machinesand much, much more! Enroll in the course and become a data scientist today!
Data Science and Machine Learning Bootcamp with R at UDEMY Curriculum
Course Introduction
Introduction to Course
Course Curriculum
What is Data Science?
Course FAQ
Course Best Practices
How to Get Help in the Course!
Installation and Set-Up
Windows Installation Set-Up
Windows Installation Procedure
Mac OS Installation Set-Up
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
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 Plotly
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:
Other courses offered by UDEMY
Student Forum
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