R Programming for Data Science

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Syed Mohiuddin

7:44:58

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1. Introduction

1. Introduction.mp4

02:17

2. What is R .mp4

02:08

3. Why Learn R .mp4

01:42

4. Features of R Language.mp4

02:03

5. Importance of R in Data Science.mp4

01:55

6. Advantages of using R.mp4

00:35

7. Applications of R Programming.mp4

02:08

8. Career Opportunities and Job Roles.mp4

01:27

2. Getting Started with R

1. Installing R Software.mp4

04:34

2. Installing RStudio.mp4

03:12

3. Look around RStudio Interface.mp4

09:08

4. Help & Examples Facility for R Features and Functions.mp4

02:51

5. Changing Look and Feel of RStudio (Optional).mp4

01:40

6. Some General Functions Good to Know.mp4

04:39

7.1 Source Code WitingFirst.R.html

7. Writing R Program using RGui.mp4

04:14

8. Writing R Program using RStudio.mp4

04:21

9.1 Source Code Comments.R.html

9. Using Comments in R Scripts.mp4

01:37

3. R Basics

1. Using R for Arithmetics.mp4

03:27

2.1 Source Code BasicComputation.R.html

2. Using Mathematical Functions.mp4

11:00

3.1 Source Code Variables.R.html

3. Variables.mp4

08:19

4. Keywords or Reserved Words.mp4

01:32

5. Simple Program to Compute Interest.mp4

04:45

6.1 Source Code VariableAssignment.R.html

6. Variable Assignments.mp4

04:50

7. Displaying Output.mp4

06:42

8. Reading Input.mp4

06:31

9. Qiuz.html

10. Quiz.html

4. Atomic Data Types

1. Statically and Dynamically Typed Languages.mp4

03:25

2.1 Source Code DataTypes.R.html

2. Atomic Data Types.mp4

03:42

3. Numeric Type.mp4

03:56

4. Integer Type.mp4

04:03

5. Complex Type.mp4

02:19

6. Logical Type.mp4

03:57

7. Character Type.mp4

05:34

8. Type Conversions.mp4

01:32

9. Conversion to Numeric Type.mp4

02:40

10. Conversion to Integer Type.mp4

03:00

11. Conversion to Complex Type.mp4

02:58

12. Conversion to Logical Type.mp4

03:45

13. Conversion to Character Type.mp4

01:52

5. Operators

1.1 Source Code RelationalOperators.R.html

1. Relational Operators.mp4

03:46

2.1 Source Code LogicalOperaotors.R.html

2. Logical Operators.mp4

04:15

6. Vectors

1.1 Source Code CreatingVectors.R.html

1. Creating Vectors.mp4

14:54

2.1 Source Code VectorIndexing.R.html

2. Subsetting Vectors.mp4

10:03

3.1 Source Code MatchingOperator.R.html

3. Matching Operator.mp4

02:55

4.1 Source Code VectorArithmetic.R.html

4. Vector Arithmetic.mp4

05:36

5.1 Source Code VectorArithmetic.R.html

5. Vector Methods & Operations.mp4

03:27

6.1 Source Code ImplicitExplicitCoercion.R.html

6. Implicit & Explicit Coercion.mp4

05:15

7.1 Source Code LogicalVectors.R.html

7. Logical Vectors.mp4

07:35

8.1 Source Code Mathematical.R.html

8. Mathematical Functions.mp4

07:39

9.1 Source Code RandomNumbers.R.html

9. Generating Random Numbers.mp4

01:43

10.1 Source Code Sequences.R.html

10. Sequences.mp4

09:39

11.1 Source Code Repitition.R.html

11. Replicate.mp4

03:42

12. Quiz.html

7. Matrices

1.1 Source Code CreatingMatrices.R.html

1. Creating Matrix.mp4

06:58

2.1 Source Code Usingdiagfunction.R.html

2. Using diag() Function.mp4

03:21

3.1 Source Code NamingRowsColumns.R.html

3. Naming Rows and Columns of Matrix.mp4

03:15

4.1 Source Code MatrixIndexing.R.html

4. Subsetting Matrix.mp4

07:56

5.1 Source Code RowColBinding.R.html

5. Martix rbind() and cbind().mp4

05:21

6.1 Source Code MatrixOperations.R.html

6. Matrix Operations.mp4

04:48

7.1 Source Code MatrixApply.R.html

7. Matrix Specific Function.mp4

04:01

8. Quiz.html

8. Lists

1.1 Source Code CreatingLists.R.html

1. Creating Lists.mp4

05:37

2.1 Source Code ListIndexing.R.html

2. Subsetting or Slicing List.mp4

05:08

3.1 Source Code NamingLists.R.html

3. Naming List & Subset Operator.mp4

02:56

4.1 Source Code ListConcatenation.R.html

4. Lists Concatenation.mp4

02:32

5. Quiz.html

9. Factors

1.1 Source Code Factors.R.html

1. Factors.mp4

02:41

10. Data Frames

1. What are Data Frames.mp4

01:54

2.1 Source Code CreatingDataframes.R.html

2. Creating Data Frames.mp4

03:56

3.1 Source Code DataFrameIndexing.R.html

3. Subseting Data Frame.mp4

07:14

4.1 Source Code Dataframesubset.R.html

4. Data Frame subset() function.mp4

05:15

5.1 Source Code Dataframerbindcbind.R.html

5. Data Frame rbind() and cbind() functions.mp4

04:23

6.1 Source Code dataframeedit.R.html

6. Data Frame edit() function.mp4

03:09

7.1 Source Code MissingValues.R.html

7. Missing Data in Data Frames.mp4

09:01

8. Quiz.html

11. Control Structures

1. Control Structures.mp4

01:32

2.1 Source Code ifelse.R.html

2. if, if-else and else-if statements.mp4

06:52

3.1 Source Code ifelsefunction.R.html

3. ifelse() function.mp4

03:32

4.1 Source Code forloop.R.html

4. for Loop.mp4

05:10

5.1 Source Code whileloop.R.html

5. while Loop.mp4

05:00

6.1 Source Code repeatloop.R.html

6. repeat Loop.mp4

04:56

7.1 Source Code breaknext.R.html

7. break & next statement.mp4

03:18

8. Quiz.html

12. Functions

1.1 Source Code Functions.R.html

1. Functions.mp4

06:15

2.1 Source Code DefaultArguments.R.html

2. Default and Named Arguments.mp4

08:34

3.1 Source Code LazyFunctions.R.html

3. Lazy Evaluation.mp4

01:40

4.1 Source Code ReturningMultipleValues.R.html

4. Functions Returning Multiple Values.mp4

02:31

5.1 Source Code InlineFunctions.R.html

5. Inline Functions.mp4

01:53

13. Importing Data in Data Frame

1.1 Dataset data.txt.html

1.2 Dataset datadollar.txt.html

1.3 Dataset dataspace.txt.html

1.4 Source Code importdatatable.R.html

1. Import Data from Text Files.mp4

04:40

2.1 Dataset data.csv.html

2.2 Source Code importdatacsv.R.html

2. Import Data from CSV Files.mp4

01:58

3.1 Dataset chicago.rds.html

3.2 Source Code ImportRDS.R.html

3. Import Data from RDS Files.mp4

01:40

4.1 Source Code ImportInternet.R.html

4. Import Data from Internet.mp4

02:25

5.1 Source Code ImportClipboard.R.html

5. Import Data from Clipboard.mp4

02:44

6.1 Source Code ExportingDataCSV.R.html

6. Exporting Data to CSV Files.mp4

02:58

7. Quiz.html

14. Data Handling using dplyr Package

1. Installing dplyr Package.mp4

02:25

2.1 Dataset murders.csv.html

2.2 Source Code dplyrselect.R.html

2. dplyr select() - Select Columns of Data Frame.mp4

06:57

3.1 Dataset murders.csv.html

3.2 Source Code dplyrfilter.R.html

3. dplyr filter() - Extract Rows from Data Frame.mp4

03:24

4.1 Dataset murders.csv.html

4.2 Source Code dplyrarrange.R.html

4. dplyr arrange() - Sort or Reorder rows of Data Frame.mp4

03:52

5.1 Dataset murders.csv.html

5.2 Source Code dplyrrename.R.html

5. dplyr rename() - Renaming Columns of Data Frame.mp4

03:52

6.1 Dataset murders.csv.html

6.2 Source Code dplyrmutate.R.html

6. dplyr mutate() - Mutate Data Frames.mp4

03:24

7.1 Dataset murders.csv.html

7.2 Source Code dplyrgroupby.R.html

7. dplyrgroup by() - Generate Summary Statistics.mp4

02:27

8.1 Dataset murders.csv.html

8.2 Source Code dplyrpipelineoperator.R.html

8. dplyr %% - Pipeline Operator.mp4

04:24

15. Data Visualization

1.1 Dataset murdersmini.csv.html

1.2 Source Code BarPlot.R.html

1. Bar Plots.mp4

04:57

2.1 Dataset murdersmini.csv.html

2.2 Source Code HorizontalBarPlots.R.html

2. Horizontal Bar Plots.mp4

03:08

3.1 Dataset GEStock.csv.html

3.2 Source Code Histogram.R.html

3. Histograms.mp4

03:27

4.1 Dataset murdersmini.csv.html

4.2 Source Code ScatterPlots.R.html

4. Scatter Plots.mp4

02:30

5.1 Dataset GEStock.csv.html

5.2 Dataset murders.csv.html

5.3 Source Code LinePlots.R.html

5. Line Plots.mp4

01:13

6.1 Dataset population.csv.html

6.2 Source Code BoxPlot.R.html

6. Box Plots.mp4

02:26

7.1 Dataset murdersmini.csv.html

7.2 Source Code StackedBarPlots.R.html

7. Stacked Bar Plots.mp4

06:43

8.1 Dataset murdersmini.csv.html

8.2 Source Code MultiplePlots.R.html

8. Multiple Plots in a Layout.mp4

07:13

16. Statistical Data Analysis

1.1 Dataset GEStock.csv.html

1.2 Dataset IBMStock.csv.html

1.3 Source Code LoadingDatasetNA.R.html

1. Exploring Stock Prices Datasets.mp4

05:00

2.1 Dataset GEStock.csv.html

2.2 Dataset IBMStock.csv.html

2.3 Source Code MinMaxRange.R.html

2. Find Highest and Lowest Stock Price and Dates.mp4

04:47

3.1 Dataset GEStock.csv.html

3.2 Dataset IBMStock.csv.html

3.3 Source Code MinMaxRange.R.html

3. Graphically Analyzing Stock Prices.mp4

07:08

4.1 Dataset GEStock.csv.html

4.2 Dataset IBMStock.csv.html

4.3 Source Code MeanMedianMode.R.html

4.4 Source Code VarianceSD.R.html

4. Analyzing Skewness of Stock Prices - Mean, Median and Standard Deviation.mp4

04:55

5.1 Dataset GEStock.csv.html

5.2 Dataset IBMStock.csv.html

5.3 Source Code VarianceSD.R.html

5. Graphically Comparing Stock Prices in same Layout.mp4

02:12

6. How to Get Certificate of Completion.mp4

00:41

Description

Learn R Programming Fundamentals, Data Wrangling, Data Visualization for Data Science

What You'll Learn?

Fundamentals of R Programming
Work with RStudio
Use Vectors, Matrices, Lists, Data Frames
Importing and Handling Large CSV files Data in R
Import packages in R & use dplyr Package for Data Wrangling
Create Data Visualization in R
Using R for Basic Statistical Data Analysis

Who is this for?

Beginner who wants to learn R Programming

What You Need to Know?

No prior knowledge or technical backgrounds is required

More details

Description
Welcome to this course of R Programming for Beginners with the hands-on tutorial, and become an R Professional which is one of the most favoured skills, that employer's need.
Whether you are new to programming or have never programmed before in R Language, this course is for you! This course covers the R Programming from scratch. This course is self-paced. There is no need to rush - you learn on your own schedule.Â
R programming language iÑ• one of the best open-source programming language and more powerful than other programming languages. It iÑ• well documented and has a clean syntax and quite ÐµÐ°Ñ•Ñƒ tÐ¾ lÐµÐ°rn.
This course will help anyone who wants to start a ÑÐ°rÐµÐµr in Data Science and Machine LÐµÐ°rning. You need to have basic undÐµrÑ•tÐ°nding Ð¾f R Programming to become a Data Scientist or Data Analyst.
This course begins with the introduction to R course that will help you write R code in no time. Then we help you with the installation of R and RStudio on your computer and setting up the programming environment. This course will provide you with everything you need to know about the basics of R Programming.
In this course we will cover the following topics:
Basics of R Programming including Operators
Fundamentals of R Programming
Vectors, Matrices, Lists
Data Frames
Importing Data in Data Frames using Text and CSV files
Data Wrangling using dplyr package
Data Visualization

This course teaches R Programming in a practical manner with hands-on experience with coding screen-cast.Â
Once you complete this course, you will be able to create or develop R Programs to solve any complex problems with ease.
Who this course is for:
Beginner who wants to learn R Programming

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Welcome to my Udemy Courses, I make programming tutorials from beginner to advanced level, I focus on creating video tutorials for programmers, software developers, engineers, and analysts.I cover topics for all skill levels, so there is something for everyone here. My focus is on Python and R programming which is applied in statistics, data analysis, data science and machine learning.

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