Update index.md

com.unity.perception/Documentation~/index.md

 # Unity Perception package (com.unity.perception)
 The Perception package provides a toolkit for generating large-scale datasets for perception-based machine learning, training and validation. It is focused on capturing ground truth for Camera-based use cases. In the future, the Perception package will include other types of sensors and machine learning tasks.
 
-[Quick Installation Instructions](SetupSteps.md)
+Visit the pages below for in-depth documentation on inidividual components of the package. 
-[Perception Tutorial](Tutorial/TUTORIAL.md)
+|Feature|Description|
+|---|---|
+|[Labeling](GroundTruthLabeling.md)|A component that marks a GameObject and its descendants with a set of labels|
+|[LabelConfig](GroundTruthLabeling.md#label-config)|An asset that defines a taxonomy of labels for ground truth generation|
+|[Perception Camera](PerceptionCamera.md)|Captures RGB images and ground truth from a [Camera](https://docs.unity3d.com/Manual/class-Camera.html).|
+|[DatasetCapture](DatasetCapture.md)|Ensures sensors are triggered at proper rates and accepts data for the JSON dataset.|
+|[Randomization (Experimental)](Randomization/Index.md)|The Randomization tool set lets you integrate domain randomization principles into your simulation.|
+
+## Getting Started
+
+**[Quick Installation Instructions](com.unity.perception/Documentation~/SetupSteps.md)**  
+Get your local Perception workspace up and running quickly. Recommended for users with prior Unity experience.
+
+**[Perception Tutorial](com.unity.perception/Documentation~/Tutorial/TUTORIAL.md)**  
+Detailed instructions covering all the important steps from installing Unity Editor, to creating your first Perception project, building a randomized Scene, and generating large-scale synthetic datasets by leveraging the power of Unity Simulation.  No prior Unity experience required.
 
 ## Preview package
 
 
 The [Unity Simulation Smart Camera Example](https://github.com/Unity-Technologies/Unity-Simulation-Smart-Camera-Outdoor) illustrates how Perception could be used in a smart city or autonomous vehicle simulation. You can generate datasets locally or at scale in [Unity Simulation](https://unity.com/products/unity-simulation).
 
-## Package contents
-
-|Feature|Description|
-|---|---|
-|[Labeling](GroundTruthLabeling.md)|A component that marks a GameObject and its descendants with a set of labels|
-|[LabelConfig](GroundTruthLabeling.md#label-config)|An asset that defines a taxonomy of labels for ground truth generation|
-|[Perception Camera](PerceptionCamera.md)|Captures RGB images and ground truth from a [Camera](https://docs.unity3d.com/Manual/class-Camera.html).|
-|[DatasetCapture](DatasetCapture.md)|Ensures sensors are triggered at proper rates and accepts data for the JSON dataset.|
-|[Randomization (Experimental)](Randomization/Index.md)|The Randomization tool set lets you integrate domain randomization principles into your simulation.|
 
 ## Known issues