diff --git a/frontend/src/pages/GettingStarted.tsx b/frontend/src/pages/GettingStarted.tsx
index bbd8dc3c9f8..94eca19e132 100644
--- a/frontend/src/pages/GettingStarted.tsx
+++ b/frontend/src/pages/GettingStarted.tsx
@@ -28,32 +28,38 @@ const options = {
 };
 
 const PAGE_CONTENT_MD = `
+<br/>
+
 ## Build your own pipeline
 
-Build an end-to-end ML pipeline with TFX  [Start Here](https://console.cloud.google.com/mlengine/notebooks/deploy-notebook?q=download_url%3Dhttps%253A%252F%252Fraw.githubusercontent.com%252Fkubeflow%252Fpipelines%252F0.1.40%252Fsamples%252Fcore%252Fparameterized_tfx_oss%252Ftaxi_pipeline_notebook.ipynb) (Alpha)
+Build an end-to-end ML pipeline with TensorFlow Extended (TFX) [**Start Here!**](https://console.cloud.google.com/mlengine/notebooks/deploy-notebook?q=download_url%3Dhttps%253A%252F%252Fraw.githubusercontent.com%252Ftensorflow%252Ftfx%252Fmaster%252Fdocs%252Ftutorials%252Ftfx%252Ftemplate.ipynb) (Alpha)
 
-## Demos and Tutorials
+<br/>
 
+## Demonstrations and Tutorials
 This section contains demo and tutorial pipelines.
 
 **Demos** - Try an end-to-end demonstration pipeline.
 
-  * [TFX pipeline demo](#/pipelines) - A trainer that does end-to-end distributed training for XGBoost models. [source code](https://github.com/kubeflow/pipelines/tree/master/samples/core/parameterized_tfx_oss)
-  * [XGBoost Pipeline](#/pipelines) - Example pipeline that does classification with model analysis based on a public taxi cab BigQuery dataset. [source code](https://github.com/kubeflow/pipelines/tree/master/samples/core/xgboost_training_cm)
+  * [TFX pipeline demo](#/pipelines) - Classification pipeline with model analysis, based on a public BigQuery dataset of taxicab trips. Learn how to [get started with TFX pipeline!](https://console.cloud.google.com/mlengine/notebooks/deploy-notebook?q=download_url%3Dhttps%253A%252F%252Fraw.githubusercontent.com%252Fkubeflow%252Fpipelines%252F0.1.40%252Fsamples%252Fcore%252Fparameterized_tfx_oss%252Ftaxi_pipeline_notebook.ipynb)
+  * [XGBoost Pipeline demo](#/pipelines) - An example of end-to-end distributed training for an XGBoost model. [source code](https://github.com/kubeflow/pipelines/tree/master/samples/core/xgboost_training_cm)
 
+<br/>
 
 **Tutorials** - Learn pipeline concepts by following a tutorial.
 
   * [Data passing in python components](#/pipelines) - Shows how to pass data between python components. [source code](https://github.com/kubeflow/pipelines/tree/master/samples/tutorials/Data%20passing%20in%20python%20components)
   * [DSL - Control structures](#/pipelines) - Shows how to use conditional execution and exit handlers. [source code](https://github.com/kubeflow/pipelines/tree/master/samples/tutorials/DSL%20-%20Control%20structures)
 
-  You can find additional tutorials and samples [here]()
+Want to learn more? [Learn from sample and tutorial pipelines.](https://www.kubeflow.org/docs/pipelines/tutorials/)
+
+<br/>
 
 ### Additional resources and documentation
-  * [TFX Landing page](https://www.tensorflow.org/tfx)
-  * [Hosted Pipeline documentation](https://cloud.google.com/ai-platform)
-  * [Troubleshooting guide](https://www.kubeflow.org/docs/pipelines/troubleshooting/)
-  * [Kubeflow Pipeline open source documentation](https://www.kubeflow.org/docs/pipelines/)
+  * [TFX documentation](https://www.tensorflow.org/tfx)
+  * [AI Platform Pipelines documentation](https://cloud.google.com/ai-platform/pipelines/docs/)
+  * [Troubleshooting guide](https://cloud.google.com/ai-platform/pipelines/docs/troubleshooting/)
+  * [Kubeflow Pipelines documentation](https://www.kubeflow.org/docs/pipelines/)
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