R master | ONLINE

About the course

What you'll learn

Learn what is Data Science and how it is helping the modern world!
What are the benefits of Data Science and Machine Learning
Able to Solve Data Science Related Problem with the Help of R Programming
Why R is a Must Have for Data Science , AI and Machine Learning!
Right Guidance of the Path if You want to be a Data Scientist + Data science Interview Preparation Guide
How to switch career in Data Science?
R Data Structure - Matrix, Array, Data Frame, Factor, List
Work with R’s conditional statements, functions, and loops
Systematically Explore data in R
Data Science Package: Dplyr , GGPlot 2
Index, slice, and Subset Data
Get your data in and out of R - CSV, Excel, Database, Web, Text Data
Data Visualization : plot different types of data & draw insights like: Line Chart, Bar Plot, Pie Chart, Histogram, Density Plot, Box Plot, 3D Plot, Mosaic Plot
Data Manipulation - Apply function, mutate(), filter(), arrange (), summarise(), groupby(), date in R
Statistics - A Must have for Data Scie

Course content

Sections: 46

•

Activities: 1

•

Resources: 267

Announcements
1. Meet Your Instructor
Files

1. Introduction to Business Analytics
3. Introduction to Machine Learning
5. Introduction To Data Scientist
7. How to switch your career into ML
9. How to switch your career into ML

1. What We are Going to Discuss Over the Course

1. Introduction to R
3. Setting up R
2. Introduction to R

1. R Programming - R Operator
2. R Conditional Statement & Loop
4. R Programming - R Function
6. R Programming - R Function #2
8. R Programming - R Function 3
Files

1. R Data Structure - Vector
4. Matrix, Array and Data Frame
8. A Deep Drive to R Data Frame
10. R Data Structure - Factor
13. R Data Structure - List
Files

1. Import CSV Data in R
4. Import Text Data in R
7. Import Excel, Web Data in R
9. Export Data in R - Text
10. Export Data in R - CSV & Exce
11. Export Data in R - CSV & Excel
Files

1. Data Manipulation - Apply Function
3. Data Manipulation - select
4. Data Manipulation - mutate
5. Data Manipulation - filter
6. Data Manipulation - arrange
8. Data Manipulation - Pipe Operator
10. Data Manipulation - group by
12. Data Manipulation - Date
Files

1. Introduction to Data Visualization & Scatter Plot
3. Data Visualization - mfrow
5. Data Visualization - Color
5. Data Visualization - pch
7. Data Visualization - Color.
7. Data Visualization - pch
9. Data Visualization - Line Chart
11. Data Visualization - Bar Plot
13. Data Visualization - Pie Chart
15. Data Visualization - Histogram
17. Data Visualization - Density Plot
19. Data Visualization - Box Plot
21. Data Visualization - Mosaic Plot and Heat Map
23. Data Visualization - 3D Plot
25. Correlation Plot and Word Cloud
27. Data Visualization - ggplot2 Part 1
28. Data Visualization - ggplot2 Part 2
30. Data Visualization - ggplot2 Part 3
Files

1. Intro To Stat - Part 1
3. Intro To Stat - Part 2
5. Intro To Stat - Part 3
7. Intro To Stat - Part 4
9. Intro To Stat - Part 5
11. Intro To Stat - Part 6
12. Intro To Stat - Part 7
14. Intro To Stat - Part 8
16. Intro To Stat - Part 9
18. Intro To Stat - Part 10
20. Intro To Stat - Part 11
Files

1. Hypothesys Testing - Part 1
3. Hypothesys Testing - Part 2
5. Hypothesys Testing - Part 3
6. Hypothesys Testing - Part 4
Files

1. Hypothesys Testing in Practice - Part 1
3. Hypothesys Testing in Practice - Part 2
4. Hypothesys Testing in Practice - Part 3
6. Hypothesys Testing in Practice - Part 4
7. Hypothesys Testing in Practice - Part 5
9. Hypothesys Testing in Practice - Part 6
10. Chi Square -Part 1
12. Chi Square -Part 2
14. ANOVA - Part 1
16. ANOVA - Part 2
17. What we discussed in the chapter so far - Summary of the Chapte
Files

1. Machine Learning Toolbox - Part 1
13. Machine Learning Toolbox/2. Machine Learning Toolbox - Part 2
3. CODES-Data Pre-Processing 1

14. Business Use Case Understaing/1. Business Case Understanding
2. CODES-Data Pre-Processing 2

1. Data Pre-Processing 1
3. Data Pre-Processing 2
5. Data Pre-Processing 3
7. Data Pre-Processing 4
8. Data Pre-Processing 5
10. Data Pre-Processing 6
11. Data Pre-Processing 7
Files

1. Linear Regression 1
12. Linear Regression 11 - Non Linear
2. Linear Regression 2
3. Linear Regression 3
4. Linear Regression 4
5. Linear Regression 5
6. Linear Regression 6.
7. Linear Regression 7 - Correlation Part 1
8. Linear Regression 7 - Correlation Part 2
9. Linear Regression 8 - Stepwise Regression.
10. Linear Regression 9 - Stepwise Regression
11. Linear Regression 10 - Dummy Variable
FILES

17. Classification Overview/1. Classification Overview

1. Logistics Regression Intuition
2. R Code Implementation -Part1
3. R Code Implementation -Part2
5. Model Evaluation.
7. Telecom Churn Case Study
9. Summary.
Files

1. K-NN Intuition
2. K-NN R Code Implementation.
4. K-NN Case Study
Files

1. Logistics Regression Intuition
2. R Code Implementation -Part1
3. R Code Implementation -Part2
5. Model Evaluation
7. Telecom Churn Case Study
9. Summary
Files

1. K-NN Intuition
2. K-NN R Code Implementation
4. K-NN Case Study
Files

1. SVM - Intuition.
2. SVM - R Code Implementation.
4. SVM - Model Tuning
6. SVM - Telecom Case Study
8. SVM - Non Separable Case
9. SVM - Pros and Cons
Files

1. Naive Bayes - Intuition
2. Naive Bayes - R Code Implementation
3. Naive Bayes - Case Study
FILES

1. SVM - Intuition
2. SVM - R Code Implementation
4. SVM - Model Tuning
6. SVM - Telecom Case Study
8. SVM - Non Separable Case and Pros and Cons
FILES

1. Decision Tree Intuition
2. Decision Tree -How it works
3. Decision Tree - R Code Implementation
4. Decision Tree - All Codes
4.1 Churn Data.csv
4.2 Decision Tree - codes.pdf

1. Naive Bayes - Intuition
2. Naive Bayes - R Code Implementation
3. Naive Bayes - Case Study
Files

1. Decision Tree Intuition
2. Decision Tree -How it works
3. Decision Tree - R Code Implementation
4. Decision Tree Pruning
5. Decision Tree Case Study
6. Decision Tree - All Codes
6.1 Churn Data.csv
6.2 Decision Tree - codes.pdf

1. Random Forest - Intuition.
2. Random Forest -R Code Implementation
3. Random Forest - Case Study
4. Codes Data Sets - Random Forest
4.1 all codes random forest 2 codes.zip

1. Capstone Project -Introduction
2. Capstone Project - Data Understanding
3. Capstone Project - Lazy Predictor
4. Capstone Project - Data Preparation
5. Capstone Project - Data Exploration
6. Capstone Project - Feature Engineering

1. Capstone Project -Introduction.mp4
2 Capstone Project Data Understanding
3. Capstone Project Lazy Predictor
4. Capstone Project Data Preparation
5. Capstone Project - Data Exploration
6. Capstone Project Feature Engineering

1. Capstone Project -Introduction.m

1. Capstone Project -Introduction
2. Capstone Project - Data Understanding
3. Capstone Project - Lazy Predictor
5. Capstone Project Data Exploration
4. Capstone Project Data Preparation
6. Capstone Project - Feature Engineering
7. Capstone Project Logistics Regression
8. Capstone Project Logistics Regression 2
9. Capstone Project Decision Tree
10. Capstone Project Random Forest
11.1 All Codes Capstone Project -Titanic Survival.zip

1. Unsupervised Learning Introduction
2. K-Mean Clustering Intuition
3. K-Mean Clustering R Code Implementation
4. K-Mean Clustering Case Study
5. All Codes K-Mean Clustering
5.1 All Codes K-Mean Clustering.zip

1. Hierarchical Clustering Intuition.
2. Hierarchical Clustering R Code Implementation
3. Hierarchical Clustering Case Study
4. All Codes - Hierarchical Clustering
4.1 All Codes - Hierarchical CLustering.zip

1. Unsupervised Learning Introduction
2. K-Mean Clustering Intuition
3. K-Mean Clustering R Code Implementation
4 K-Mean Clustering Case Study
5. All Codes K-Mean Clustering
5.1 All Codes K-Mean Clustering.zip

1. DBScan Clustering -Intuition and R Code
1. DBScan Clustering -Intuition and R Code (copy)
3. All codes - DBScan Clustering
3.1 All Codes DBScan Clustering.zip

1. Hierarchical Clustering Intuition
2. Hierarchical Clustering R Code Implementation
3. Hierarchical Clustering Case Study
4. All Codes - Hierarchical Clustering
4.1 All Codes - Hierarchical CLustering.zip

1. DBScan Clustering -Intuition and R Code
2. DBScan Clustering Case Study
3. All codes - DBScan Clustering
3.1 All Codes DBScan Clustering.zip

1. PCA - Intuition
2. PCA - R Code Implementation
3. PCA - Case Study
4. All Codes - PCA
4.1 All codes Principal Component Analysis.zip

1. Association Rule Mining -Introduction
2. Association Rule MiningR Code Implementation
3. Association Rule Mining - Pre-Processing
4. Association Rule Mining - Case Study

1. Big Mart Sale - Data Structure
2. Big Mart Sale - Univariate Analysis
3. Big Mart Sale - Bi-Variate Analysis.
4. Big Mart Sale - Fetature Engineering
5. Big Mart Sale - Pre-Processing.
6. Big Mart Sale - Model Building & Evaluation
7. Capstone Project - Big Mart Sell All Codes
7.1 all code big mart sell.zip
7.2 all code big mart sell.zip
XLSx

1. Big Mart Sale - Data Structure
2. Big Mart Sale Univariate Analysis
3. Big Mart Sale - Bi-Variate Analysis
. Big Mart Sale - Fetature Engineering
5. Big Mart Sale - Pre-Processing
6. Big Mart Sale - Model Building & Evaluation
7. Capstone Project - Big Mart Sell All Codes
7.1 Big Mart Sale 4 files.zip

1. Model Deployment - Workflow
2. Model Deployment - Pre Requisite
3. Model Deployment - Steps To Follow
4. Model Deployment - Azure ML DEMO

1. All Bonus - Interview Preparation + PDF + Private Group

1. Model Deployment - Workflow
2. Model Deployment - Pre Requisite
3. Model Deployment Steps To Follow
4. Model Deployment - Azure ML DEMO.mp4]

1. All Bonus - Interview Preparation + PDF + Private Group

Enrolment options

Data Science Masterclass With R! 4 Projects+8 Case Studies

Course modified date: 9 Feb 2024

What you'll learn

Learn what is Data Science and how it is helping the modern world!
What are the benefits of Data Science and Machine Learning
Able to Solve Data Science Related Problem with the Help of R Programming
Why R is a Must Have for Data Science , AI and Machine Learning!
Right Guidance of the Path if You want to be a Data Scientist + Data science Interview Preparation Guide
How to switch career in Data Science?
R Data Structure - Matrix, Array, Data Frame, Factor, List
Work with R’s conditional statements, functions, and loops
Systematically Explore data in R
Data Science Package: Dplyr , GGPlot 2
Index, slice, and Subset Data
Get your data in and out of R - CSV, Excel, Database, Web, Text Data
Data Visualization : plot different types of data & draw insights like: Line Chart, Bar Plot, Pie Chart, Histogram, Density Plot, Box Plot, 3D Plot, Mosaic Plot
Data Manipulation - Apply function, mutate(), filter(), arrange (), summarise(), groupby(), date in R
Statistics - A Must have for Data Scie

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Data Science Masterclass With R! 4 Projects+8 Case Studies

About the course

What you'll learn

Course content

Instructors

Enrolment options

Data Science Masterclass With R! 4 Projects+8 Case Studies

What you'll learn

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