Update README.md

Author: ishaghosh27

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

@@ -2,8 +2,9 @@
 
 The oneAPI Collective Communications Library Bindings for PyTorch* (oneCCL Bindings for PyTorch*) holds PyTorch bindings maintained by Intel for the Intel® oneAPI Collective Communications Library (oneCCL).
 
-| Area                  | Description
+| Property              | Description
 |:---                   |:---
+| Category              | Getting Started
 | What you will learn   | How to get started with oneCCL Bindings for PyTorch*
 | Time to complete      | 60 minutes
 
@@ -34,8 +35,56 @@ The Jupyter Notebook also demonstrates how to change PyTorch* distributed worklo
 >- [Intel® oneCCL Bindings for PyTorch*](https://github.com/intel/torch-ccl) 
 >- [Distributed Training with oneCCL in PyTorch*](https://github.com/intel/optimized-models/tree/master/pytorch/distributed)
 
+## Environment Setup
+You will need to download and install the following toolkits, tools, and components to use the sample.
+<!-- Use numbered steps instead of subheadings -->
 
-## Run the `oneCCL Bindings for PyTorch* Getting Started` Sample
+**1. Get AI Tools**
+
+Required AI Tools: < ><!-- List specific AI Tools that needs to be installed before running this sample --> 
+
+If you have not already, select and install these Tools via [AI Tools Selector](https://www.intel.com/content/www/us/en/developer/tools/oneapi/ai-tools-selector.html). AI and Analytics samples are validated on AI Tools Offline Installer. It is recommended to select Offline Installer option in AI Tools Selector.
+
+>**Note**: If Docker option is chosen in AI Tools Selector, refer to [Working with Preset Containers](https://github.com/intel/ai-containers/tree/main/preset) to learn how to run the docker and samples.
+
+**2. (Offline Installer) Activate the AI Tools bundle base environment**
+<!-- this step is from AI Tools GSG, please don't modify unless GSG is updated -->
+If the default path is used during the installation of AI Tools:
+```
+source $HOME/intel/oneapi/intelpython/bin/activate
+```
+If a non-default path is used:
+```
+source <custom_path>/bin/activate
+```
+ 
+**3. (Offline Installer) Activate relevant Conda environment**
+<!-- specify relevant conda environment name in Offline Installer for this sample -->
+```
+conda activate <offline-conda-env-name>  
+``` 
+
+**4. Clone the GitHub repository**
+<!-- for oneapi-samples: git clone https://github.com/oneapi-src/oneAPI-samples.git
+cd oneAPI-samples/AI-and-Analytics/<samples-folder>/<individual-sample-folder> -->
+<!-- for migrated samples - provide git clone command for individual repo and cd to sample dir --> 
+``` 
+git clone <link-to-the-repo>.git
+cd <path-to-sample-dir>
+```
+
+**5. Install dependencies**
+<!-- It is required to have requirement.txt file in sample dir. It should list additional libraries, such as matplotlib, ipykernel etc. -->
+>**Note**: Before running the following commands, make sure your Conda/Python environment with AI Tools installed is activated
+
+```
+pip install -r requirements.txt
+pip install notebook
+``` 
+For Jupyter Notebook, refer to [Installing Jupyter](https://jupyter.org/install) for detailed installation instructions.
+
+## Run the Sample
+>**Note**: Before running the sample, make sure [Environment Setup](https://github.com/oneapi-src/oneAPI-samples/tree/master/AI-and-Analytics/Getting-Started-Samples/INC-Quantization-Sample-for-PyTorch#environment-setup) is completed.
 
 Go to the section which corresponds to the installation method chosen in [AI Tools Selector](https://www.intel.com/content/www/us/en/developer/tools/oneapi/ai-tools-selector.html) to see relevant instructions:
 * [AI Tools Offline Installer (Validated)](#ai-tools-offline-installer-validated)
@@ -50,23 +99,17 @@ If you used a separate location, open a terminal and type the following
 ```
 source <custom_path>/bin/activate
 ```
-2. Clone the GitHub repository and install required packages:
-``` 
-git clone https://github.com/oneapi-src/oneAPI-samples.git
-cd oneAPI-samples/AI-and-Analytics/Getting-Started-Samples/Intel_oneCCL_Bindings_For_PyTorch_GettingStarted/
-pip install -r requirements.txt
-```
-3. Launch Jupyter Notebook.
+2. Launch Jupyter Notebook.
 ```
 jupyter notebook --ip=0.0.0.0 --port 8888 --allow-root
 ```
-4. Follow the instructions to open the URL with the token in your browser.
-5. Locate and select the Notebook.
+3. Follow the instructions to open the URL with the token in your browser.
+4. Select the Notebook.
      ```
      oneCCL_Bindings_GettingStarted.ipynb
      ```
-6. Change your Jupyter Notebook kernel to **PyTorch** or **PyTorch-GPU**.
-7. Run every cell in the Notebook in sequence.
+5. Change kernel to **PyTorch** or **PyTorch-GPU**.
+6. Run every cell in the Notebook in sequence.
 
 ### Docker
 AI Tools Docker images already have Get Started samples pre-installed. Refer to [Working with Preset Containers](https://github.com/intel/ai-containers/tree/main/preset) to learn how to run the docker and samples.
@@ -77,3 +120,5 @@ Code samples are licensed under the MIT license. See
 [License.txt](https://github.com/oneapi-src/oneAPI-samples/blob/master/License.txt) for details.
 
 Third party program Licenses can be found here: [third-party-programs.txt](https://github.com/oneapi-src/oneAPI-samples/blob/master/third-party-programs.txt).
+
+*Other names and brands may be claimed as the property of others. [Trademarks](https://www.intel.com/content/www/us/en/legal/trademarks.html)