diff --git a/website/www/site/content/en/get-started/_index.md b/website/www/site/content/en/get-started/_index.md
index 8aa6ff626c42..e6dfbc8ef2a3 100644
--- a/website/www/site/content/en/get-started/_index.md
+++ b/website/www/site/content/en/get-started/_index.md
@@ -21,7 +21,9 @@ limitations under the License.
 
 # Get Started with Apache Beam
 
-Learn how to use Beam to create data processing pipelines that run on supported processing back-ends.
+Learn how to use Beam to create data processing pipelines that run on supported processing back-ends. More learning resources are [here](https://beam.apache.org/get-started/resources/learning-resources/).
+
+You can also get a Beam badge now if you pass [this quest](https://beam.apache.org/get-started/resources/learning-resources/#certifications)!
 
 ## Tour of Beam
 
@@ -29,6 +31,10 @@ Learn how to use Beam to create data processing pipelines that run on supported
 Topics include core Beam concepts, from simple to advanced.
 You can try examples, do exercises, and solve challenges along the learning journey.
 
+## Beam Playground
+
+[Beam Playground](https://play.beam.apache.org) is an interactive environment to try out Beam transforms and examples without having to install Apache Beam in your environment.
+
 ## Beam Overview
 
 Read the [Apache Beam Overview](/get-started/beam-overview) to learn about the Beam model,
diff --git a/website/www/site/content/en/get-started/resources/learning-resources.md b/website/www/site/content/en/get-started/resources/learning-resources.md
index 14bd90ee80b9..b983071401bb 100644
--- a/website/www/site/content/en/get-started/resources/learning-resources.md
+++ b/website/www/site/content/en/get-started/resources/learning-resources.md
@@ -151,11 +151,16 @@ complexity. Beam Katas are available for both Java and Python SDKs.
 
 ## Code Examples {#code-examples}
 
+### Dataflow Cookbook
+
+The [cookbook](https://github.com/GoogleCloudPlatform/dataflow-cookbook) includes examples in Java, Python, and Scala (via Scio), provides ready-to-launch and self-contained Beam pipelines.
+
 ### Java
 
 *   **[Snippets 1](https://github.com/apache/beam/tree/master/examples/java/src/main/java/org/apache/beam/examples/cookbook)** - Commonly-used data analysis patterns such as how to use [BigQuery](https://cloud.google.com/bigquery), a CombinePerKey transform, remove duplicate lines in files, filtering, joining PCollections, getting the maximum value of a PCollection, etc.
 *   **[Snippets 2](https://github.com/apache/beam/tree/master/examples/java/src/main/java/org/apache/beam/examples/common)** - Additional examples on common tasks such as configuring [BigQuery](https://cloud.google.com/bigquery), [PubSub](https://cloud.google.com/pubsub/), writing one file per window, etc.
 *   **[Complete Examples](https://github.com/apache/beam/tree/master/examples/java/src/main/java/org/apache/beam/examples/complete)** - End-to-end example pipelines such as an auto complete, a streaming word extract, calculating the Term Frequency-Inverse Document Frequency ([TF-IDF](https://en.wikipedia.org/wiki/Tf%E2%80%93idf)), getting the top Wikipedia sessions, traffic max lane flow, traffic routes, etc.
+*   **[Pub/Sub to BigQuery](https://github.com/GoogleCloudPlatform/cloud-code-samples/tree/v1/java/java-dataflow-samples/read-pubsub-write-bigquery)** - A complete example demonstrates using Apache Beam on Dataflow to convert JSON encoded Pub/Sub subscription message strings into structured data and write that data to a BigQuery table.
 
 ### Python