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Update readme.md- R
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sau-mili authored May 29, 2024
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- [Beginner Level Projects](#beginner-level-projects)
- [Intermediate Level Projects](#intermediate-level-projects)
- [Advanced Level Projects](#advanced-level-projects)
- [Additional Tips](#additional-tips)
- [Version Control](#version-control)
- [YouTube](#youtube)
- [YouTube Channels to Learn R](#youtube-channels-to-learn-r)
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### Tutorials
> Start your journey into R programming with these essential tutorials covering basic syntax and concepts.
### Introduction
#### Introduction

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### Fundamentals
#### Fundamentals

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</table>

### Data Manipulation
#### Data Manipulation

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### Data Visualization
#### Data Visualization
<table width="100%">
<tr>
<th>Resource Name</th>
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</table>

### Statistical Analysis
#### Statistical Analysis

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### Machine Learning
#### Machine Learning

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### Deep Learning
#### Deep Learning

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### Reproducible Research
#### Reproducible Research
<table width="100%">
<tr>
<th>Resource Name</th>
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</tr>
</table>

## Tools and Development Environment
### Tools and Development Environment
> Here are somme tools and development environments for R programming.
## Rstudio
#### Rstudio

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### IDEs for R
#### IDEs for R
<table width="100%">
<tr>
<th>Resource Name</th>
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</table>

### Online Editors for R
#### Online Editors for R
<table width="100%">
<tr>

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</table>

### RMarkdown
#### RMarkdown

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</tr>
</table>

## R Packages and Libraries
### R Packages and Libraries

> Packages in R Programming language are a set of R functions, compiled code, and sample data. These are stored under a directory called “library” within the R environment
### Data Manipulation Packages
#### Data Manipulation Packages

<table width="100%">
<tr>
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### Data Visualization Packages
#### Data Visualization Packages

<table width="100%">
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</tr>
</table>

### Statistical Analysis Packages
#### Statistical Analysis Packages

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</tr>
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## Advanced Topics
> Here are some advance topics in R which you can consider to enhance your mastery in R programming.
### Advanced Topics
> Here are some advanced topics in R that you can consider to enhance your mastery in R programming.
### R for Big Data
#### R for Big Data

<table width="100%">
<tr>
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</table>

### Parallel Computing
#### Parallel Computing


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</table>

### Advanced Statistical Modeling
#### Advanced Statistical Modeling


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</tr>
</table>

## Specialized Topics
### Specialized Topics
> Here are some specialized topics
### Bioinformatics
#### Bioinformatics
<table width="100%">
<tr>
<th>Resource Name</th>
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</tr>
</table>

### Time Series Analysis
#### Time Series Analysis
<table width="100%">
<tr>
<th>Resource Name</th>
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</tr>
</table>

### Geospatial Analysis
#### Geospatial Analysis
<table width="100%">
<tr>
<th>Resource Name</th>
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</tr>
</table>

## R Projects
### R Projects
> Here are some projrct ideas for R programming from beginner level to advance level.
### Beginner Level Projects
#### Beginner Level Projects
<table width="100%">
<tr>
<th>Resource Name</th>
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</tr>
</table>

### Intermediate Level Projects
#### Intermediate Level Projects
<table width="100%">
<tr>
<th>Resource Name</th>
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</tr>
</table>

### Advanced Level Projects
#### Advanced Level Projects

<table width="100%">
<tr>
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</tr>
</table>

## Youtube
### Youtube
> Here are some youtube channels which you can refer.
### YouTube Channels to Learn R
#### YouTube Channels to Learn R
<table width="100%">
<tr>
<th>Resource Name</th>
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</tr>
</table>

### YouTube Playlists for Learning R
#### YouTube Playlists for Learning R

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</table>


## Courses
### Courses
> Here are some courses.
### Free Certification Courses
#### Free Certification Courses
<table width="100%">
<tr>
<th>Resource Name</th>
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</table>

### Paid Certification Courses
#### Paid Certification Courses

<table width="100%">
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</table>

## Additional Resources
### Additional Resources
> Additional resources which may help you in your development journey.
### R Communities
#### R Communities
<table width="100%">
<tr>
<th>Resource Name</th>
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</tr>
</table>

### R Books
#### R Books
<table width="100%">
<tr>
<th>Resource Name</th>
<th>Description</th>
<th>Cost</th>
</tr>
<tr>
<td><a href="https://www.amazon.com/R-Cookbook-OReilly-Cookbooks-Paul/dp/0596809158">R Cookbook</a></td>
<td>R Cookbook By Paul Teetor</td>
<td>Paid</td>
</tr>
<tr>
<td><a href="https://www.amazon.com/Art-R-Programming-Statistical-Software/dp/1593273843">The Art of R Programming</a></td>
<td>The Art of R Programming By Norman Matloff</td>
<td>Paid</td>
</tr>
<tr>
<td><a href="https://www.amazon.com/Using-Introductory-Statistics-Chapman-Hall/dp/1466590734/ref=sr_1_1?dib=eyJ2IjoiMSJ9.MMC8KySF3vodrO7L2zv7Yio8DBHC_g5s2wyesdWehPukRBAveLVCIyFOvOtPKsSiHD99ZOYcy9nP9alRyEAzMHd_88g8IIHX3caM4FHQqxj-h4cjuQkTu2DMfp-7hz0ECeZwfkWeWnkrnyt1ixI2a204gE0L08TjfPeKbOo1giNkZaFo-JRmGEj8RM0RyKC0sSuQHzczbVpCeTh_u_J8wrPRwyS50Fv_Kn9_mXM5LbI.ovYaXCXqfsjec20Q7Lw_jEoruAC9gUsBBNgd0xfcmN4&dib_tag=se&keywords=Introductory-Statistics-Using-R&qid=1716470344&sr=8-1">Introductory Statistics with R</a></td>
<td>Introductory Statistics with R By John Verzani</td>
<td>Paid</td>
</tr>
<tr>
<td><a href="https://www.amazon.com/Hands-Programming-Writing-Functions-Extending/dp/1449359019">Hands-On Programming with R</a></td>
<td>Advanced R By Garrett Grolemund</td>
<td>Paid</td>
</tr>
<tr>
<td><a href="https://www.amazon.com/Advanced-R-Hadley-Wickham/dp/1466586966">Advanced R</a></td>
<td>By Hadley Wickham</td>
<td>Paid</td>
</tr>
</table>

## Conclusion
### Conclusion

R programming is an indispensable tool for data analysis, statistics, and visualization. The extensive range of resources provided in this guide aims to facilitate your learning journey, from mastering the basics to exploring advanced techniques. With the right combination of tutorials, coding platforms, and tools, you can develop a strong proficiency in R and leverage its capabilities for your data-driven projects.

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