LL ID #3984: Last Updates (#674)

* Self-QA Updates

Adding workshop changes to further align with the Self-QA checklist.

* Update adb-free-container-setup.md

* Post-Testing Edits V1

* Update adb-free-container-setup.md

* Post-Testing Changes V2

* Updating Screenshots

* WMSID# 11693: Adding the initial workshop structure.

* Update adb-free-container-setup.md

* Update adb-free-container-setup.md

* [WMS ID #11029] DB Collective - JSON Duality Search

* WMS ID #11029: Minor fix

* Update manifest.json

* LL ID #4004: Add JSON Duality Intro

* LL ID# 4004: Minor Updates

* LL ID #4004: Minor updates.

* WMS ID #11693: Revising the workshop structure.

* WMS ID# 11693

* HOL 46

* DB Collective - JSON Updates

* LL ID #4004: DB Collective Changes

* OCW & DB Collective Updates

* Update new-duality-views-15.md

* Update new-duality-views-15.md

* Update new-duality-views-15.md

* Update new-duality-views-15.md

* Update new-duality-views-15.md

* Update new-duality-views-15.md

* LL ID #3984: Formatting Changes

* HOL 46 Technical Fixes

* Update inst-auth-container-setup.md

* DB Collective + OCW 24 Updates

* Update manifest.json

* LL ID #3984: Screenshots & Minor Fixes

* LL ID #3984 - Minor Updates & Fixes

* Last updates.

* Update similarity-search.md

* Update intro-aivs-adb.md

---------

Co-authored-by: William Masdon <william.masdon@oracle.com>
Co-authored-by: Hope Fisher <127253314+hope-fisher@users.noreply.github.com>
Co-authored-by: Dan Wiliams <127415766+dannymgithub@users.noreply.github.com>

23aifree/introduction/intro-aivs-adb.md

@@ -11,7 +11,7 @@ Oracle Autonomous Database provides an easy-to-use, fully autonomous database th
 
 The Oracle Autonomous Database Free Container Image provides an alternative to run Autonomous Database in a container in your own environment, without requiring access to Oracle Cloud Infrastructure Console or to the internet. When you run Autonomous Database in a container, the container provides a local, isolated environment with additional options for development, testing, and exploration of Oracle Autonomous Database features.
 
-Learrn more about the Oracle Autonomous Database Free container image [here](https://docs.oracle.com/en-us/iaas/autonomous-database-serverless/doc/autonomous-docker-container.html)
+Learn more about the Oracle Autonomous Database Free container image [here](https://docs.oracle.com/en-us/iaas/autonomous-database-serverless/doc/autonomous-docker-container.html).
 
 **_Estimated Time: 90 minutes_**
 

23aifree/vector-search/similarity-search.md

@@ -12,7 +12,7 @@ In this lab, you will:
 * Configure your workspace to use Oracle AI Vector Search.
 * Load a vector embedding model.
 * Vectorize the sample data.
-* Leverage your business data with vector search. 
+* Query the vector data with Oracle AI Vector Search.
 
 ### **Prerequisites**
 This lab assumes you have:
@@ -92,7 +92,7 @@ This lab assumes you have:
         FROM co.products;
     </copy>
     ```
-    ![Generate description vectors.](images/generate-vectors.png)
+    ![Generate description vectors.](images/create-product-vectors.png)
 
 2. **Using vector search, retrieve the 5 products most similar to the word "professional".** By default, VECTOR_DISTANCE uses the cosine formula as it's distance metric, but you can change the metric as you see fit. We recommend using the metric suggested by the embedding model, in this case it was cosine. Learn more about distance metrics [here](https://docs.oracle.com/en/database/oracle/oracle-database/23/vecse/vector-distance-metrics.html).
     ```
@@ -120,9 +120,8 @@ This lab assumes you have:
     Once again--big improvements! Notice that the model was able to relate slacks to other bottoms, and use the term's professional context to find other formal wear. So, despite there not being a product description containing the word "slacks", viable results are still returned due to their similarity to the query. 
     ![Similarity search on the word slacks.](images/similarity-search-slacks.png)
 
-**You've completed the workshop!**
-<!-- ## Task 3: Combine Business Data with Similarity Search -->
-<!-- You may now proceed to the next lab. -->
+
+**Congratulations! You've completed the workshop.**
 
 ## Acknowledgements
 - **Authors** - Brianna Ambler, Database Product Management