Update Readme (oneapi-src#736)

Changed URL for installation.

Author: bdmoore1

AI-and-Analytics/Getting-Started-Samples/IntelModin_GettingStarted/README.md

@@ -1,21 +1,21 @@
 # `Intel Modin Getting Started` Sample
-This Getting Started sample code shows how to use distributed Pandas using the Intel® Distribution of Modin* package. It demonstrates how to use software products that can be found in the [Intel® oneAPI AI Analytics Toolkit](https://software.intel.com/content/www/us/en/develop/tools/oneapi/ai-analytics-toolkit.html). 
+This Getting Started sample code shows how to use distributed Pandas using the Intel® Distribution of Modin* package. It demonstrates how to use software products that can be found in the [Intel® oneAPI AI Analytics Toolkit](https://software.intel.com/content/www/us/en/develop/tools/oneapi/ai-analytics-toolkit.html).
 
 | Optimized for                     | Description
 | :---                              | :---
 | OS                                | 64-bit Linux: Ubuntu 18.04 or higher
-| Hardware                          | Intel Atom® Processors; Intel® Core™ Processor Family; Intel® Xeon® Processor Family; Intel® Xeon® Scalable processor family
+| Hardware                          | Intel Atom® Processors; Intel® Core™ Processor Family; Intel® Xeon® Processor Family; Intel® Xeon® Scalable Performance Processor Family
 | Software                          | Intel Distribution of Modin*, Intel® oneAPI AI Analytics Toolkit
 | What you will learn               | Basic Intel Distribution of Modin* programming model for Intel CPU
 | Time to complete                  | 5-8 minutes
 
 ## Purpose
-Intel Distribution of Modin* uses Ray or Dask to provide an effortless way to speed up your Pandas notebooks, scripts, and libraries. Unlike other distributed DataFrame libraries, Intel Distribution of Modin* provides seamless integration and compatibility with existing Pandas code. 
+Intel Distribution of Modin* uses Ray or Dask to provide an effortless way to speed up your Pandas notebooks, scripts, and libraries. Unlike other distributed DataFrame libraries, Intel Distribution of Modin* provides seamless integration and compatibility with existing Pandas code.
 
 In this sample, you will run Intel Distribution of Modin*-accelerated Pandas functions and note the performance gain when compared to "stock" (aka standard) Pandas functions.
 
 ## Key Implementation Details
-This Getting Started sample code is implemented for CPU using the Python language. The example assumes you have Pandas and MoIntel Distribution of Modin* installed inside a conda environment, similar to what is directed by the [Intel® oneAPI AI Analytics Toolkit](https://software.intel.com/content/www/us/en/develop/articles/installing-ai-kit-with-conda.html). 
+This Getting Started sample code is implemented for CPU using the Python language. The example assumes you have Pandas and MoIntel Distribution of Modin* installed inside a conda environment, similar to what is directed by the [Intel® oneAPI AI Analytics Toolkit](https://www.intel.com/content/www/us/en/develop/documentation/installation-guide-for-intel-oneapi-toolkits-linux/top/installation/install-using-package-managers/conda/install-intel-ai-analytics-toolkit-via-conda.html).
 
 ## License
 
@@ -26,11 +26,11 @@ Third party program Licenses can be found here: [third-party-programs.txt](https
 
 ## Building Intel Distribution of Modin* for CPU
 
-Intel® Distribution of Modin* is ready for use once you finish the Intel® Distribution of Modin* installation and have run the post installation script.
+Intel Distribution of Modin* is ready for use once you finish the Intel Distribution of Modin installation and have run the post installation script.
 
-For this sample, you will also have to install the matplotlib module. 
+For this sample, you will also have to install the matplotlib module.
 
-Please install matplotlib with the command: 
+Please install matplotlib with the command:
 
 ```
 conda install -c intel matplotlib
@@ -41,7 +41,7 @@ You can refer to the oneAPI [main page](https://software.intel.com/en-us/oneapi)
 
 ### Activate conda environment With Root Access
 
-Please follow the Getting Started Guide steps (above) to set up your oneAPI environment with the `setvars.sh` script and [Intel® Distribution of Modin* environment installation] (https://software.intel.com/content/www/us/en/develop/articles/installing-ai-kit-with-conda.html). Then navigate in Linux shell to your oneapi installation path, typically `/opt/intel/oneapi/` when installed as root or sudo, and `~/intel/oneapi/` when not installed as a superuser. If you customized the installation folder, the `setvars.sh` file is in your custom folder.
+Please follow the Getting Started Guide steps (above) to set up your oneAPI environment with the `setvars.sh` script and [Intel Distribution of Modin environment installation](https://www.intel.com/content/www/us/en/develop/documentation/installation-guide-for-intel-oneapi-toolkits-linux/top/installation/install-using-package-managers/conda/install-intel-ai-analytics-toolkit-via-conda.html). Then navigate in Linux shell to your oneapi installation path, typically `/opt/intel/oneapi/` when installed as root or sudo, and `~/intel/oneapi/` when not installed as a superuser. If you customized the installation folder, the `setvars.sh` file is in your custom folder.
 
 Activate the conda environment with the following command:
 
@@ -91,7 +91,7 @@ Open .ipynb file and run cells in Jupyter Notebook using the "Run" button (see t
 
 ![Click the Run Button in the Jupyter Notebook](Jupyter_Run.jpg "Run Button on Jupyter Notebook")
 
-#### Intel® DevCloud for oneAPI JupyterLab 
+#### Intel® DevCloud for oneAPI JupyterLab
 
 Please note that as of right now, this sample cannot be run on Intel® DevCloud for oneAPI JupyterLab due to conflicts between the Intel® DevCloud for oneAPI JupyterLab platform and Modin dependencies. This is a known issue that Intel is currently working on resolving. Thank you for your patience.