PR for Building Block (blocks) and Tasks for oml (#470)

* oml blocks and tasks updated

* Masked texts in images

Masked tenancy names in screenshots.

* Removed "proceed to next lab"

* Updated oml notebooks ea file.

* Updated oml-notebooks-ea.md file

* Provided url to the Conda topic

Provided url to the Conda interpreter topic in OMLUG.

* Update oml-notebooks-ea.md

* new task added

New task on signing into oml from livelabs environment added

* Removed advance tasks to be added to another lab

* Updated notebook-ea block

* oml-notebook-ea updated

* Screenshot updated

The Notebook Classics entry removed from left nav

* SS updated

* Intro edited

* Visualization and Notebooks block updated

Prod URL added to redirect the user to the new lab "Advanced Options in OML Notebooks" along with other edits

* Update oml-notebooks-ea.md

Link added to Adv OML NB lab

* Update oml-nb-visualizations.md

Visualization intro added

* URL updated

* Added new block in oml - automl

* Screenshot replaced to show new UI

Launchpad > Dev > Machine Learning.

* New screenshot added for ADB tool Config tab

Text modified accordingly

* Updated OML NB block

Added the Task "Create a Notebook using a Template Example". Modified SS as applicable.

* Update oml-notebooks-ea.md

removed duplicate content.

* Update oml-notebooks-ea.md

Dated updated

* Modified screenshots to sync NB listings

OML Notebooks lab

* Update oml-notebooks-ea.md

Content updated

* task provision an adb updated with redwood screenshots

* Task on create an OMLUSER updated with redwood UI

* Screenshots updated

* SS updated

* oml-notebook-ea updated

Since for freetier, the user already created and signed in the previous lab

* Update oml-notebooks-ea.md

Content updated wrt freetier setup in Lab 1

* Prov an ADB topic updated

* Screenshots replaced

* Screenshot replaced

* Screenshots added to show Redwood themed UI

* provision an adb topic edited

* Content on tags updated

* References to sign in topics (tasks) updated

* oml-notebook lab updated

* oml-notebook-ea updated

* Addressed the comments by MH.

* OML UI description updated

* Upper case

* Screenshot updated

Screenshot updated to hide "console exp" banner

* oml-notebooks-ea updated

* oml-notebook-ea updated

Minor edit

* oml-monitoring.md file updated to address comments by Marcos.

* Date updated to June

* Rebranded

Changed all instanced of Autonomous Database to Autonomous AI Database

* Screenshots replaced for rebranding

* Screenshot updated

Rebranded

* Rebranding

* Changed 23ai to 26ai. Rebranding

* Screenshot replaced to show 26ai

* Screenshot replaced

Author: MoitreyeeHazarika

building-blocks/blocks/oml/oml-automl/oml-automl.md

@@ -32,7 +32,7 @@ This lab assumes you have:
 
 ## Task 1: Access Oracle Machine Learning AutoML UI
 
-To access AutoML UI, you must sign into the Oracle Machine Learning User Interface, which also includes Oracle Machine Learning notebooks, on Autonomous Database:
+To access AutoML UI, you must sign into the Oracle Machine Learning User Interface, which also includes Oracle Machine Learning notebooks, on Autonomous AI Database:
 
 1. Sign into Oracle Machine Learning user interface (following Lab1, Task 1 instructions).
 
@@ -93,7 +93,7 @@ To create an Experiment:
 	*  **High** level gives the greatest parallelism but significantly limits the number of concurrent jobs.
 	*  **Medium** level enables some parallelism but allows greater concurrency for job processing.
 
-	> **Note:** Changing the database service level setting on the Always Free Tier will have no effect since there is a 1 OCPU limit. However, if you increase the OCPUs allocated to your autonomous database, then you can increase the Database Service Level to Medium or High.
+	> **Note:** Changing the database service level setting on the Always Free Tier will have no effect since there is a 1 OCPU limit. However, if you increase the OCPUs allocated to your Autonomous AI Database, then you can increase the Database Service Level to Medium or High.
 
 13. Leave the default algorithms selected. 
 
@@ -331,6 +331,6 @@ You may now **proceed to the next lab**.
 
 ## Acknowledgements
 
-* **Author** - Moitreyee Hazarika, Principal User Assistance Developer, Database User Assistance Development
+* **Author** - Moitreyee Hazarika, Consulting User Assistance Developer, Database User Assistance Development
 * **Contributors** -  Mark Hornick, Senior Director, Data Science and Machine Learning; Marcos Arancibia, Senior Principal Product Manager, Machine Learning; Sherry LaMonica, Consulting Member of Tech Staff, Machine Learning
-* **Last Updated By/Date** - Moitreyee Hazarika, June 2025
+* **Last Updated By/Date** - Moitreyee Hazarika, October 2025

building-blocks/blocks/oml/oml-conda/oml-conda.md

@@ -159,12 +159,12 @@ To create a Conda environment named _myrenv_ with R-4.0.5 for OML4R compatibilit
 	![Command to view the R conda environment](images/view-myrenv.png)
 	Note that the _myrenv_ environment is now listed along with the _mypyenv_ in the output. Note that the asterisk (*) is against the _mypyenv_, indicating that this environment is active currently.
 
-## Task 3: Upload the Conda environments to an Object Storage bucket associated with the Autonomous Database
-In this task, you will upload the environments _mypyenv_ and _myrenv_ to the Object Storage bucket associated with the Autonomous Database instance using the `upload` command. You will provide environment descriptions and tags, one for the user name and one for the application name. You will also overwrite any environment with the same name if it exists.
+## Task 3: Upload the Conda environments to an Object Storage bucket associated with the Autonomous AI Database
+In this task, you will upload the environments _mypyenv_ and _myrenv_ to the Object Storage bucket associated with the Autonomous AI Database instance using the `upload` command. You will provide environment descriptions and tags, one for the user name and one for the application name. You will also overwrite any environment with the same name if it exists.
 
 The application tag is required for use with embedded execution. For example, OML4Py embedded Python execution works with Conda environments containing the OML4PY tag.
 
->*Note:* There is one Object Storage bucket for each data center region. The Conda environment is saved to a folder in Object Storage corresponding to the tenancy and database. The folder is managed by Autonomous Database and is only available to users through OML Notebooks. There is an 8G maximum size for a single Conda environment, and no size limit on Object Storage.
+>*Note:* There is one Object Storage bucket for each data center region. The Conda environment is saved to a folder in Object Storage corresponding to the tenancy and database. The folder is managed by Autonomous AI Database and is only available to users through OML Notebooks. There is an 8G maximum size for a single Conda environment, and no size limit on Object Storage.
 
 
 1. Run the following command to upload the mypyenv to the Object Storage bucket associated with the ADB.
@@ -353,6 +353,6 @@ The steps in task 5 must be performed as the non-ADMIN OML user with the `OML_DE
 
 ## Acknowledgements
 
-* **Author** -  Moitreyee Hazarika, Principal User Assistance Developer, Database User Assistance Development
+* **Author** -  Moitreyee Hazarika, Consulting User Assistance Developer, Database User Assistance Development
 * **Contributors** -   Mark Hornick, Senior Director, Data Science and Machine Learning; Marcos Arancibia Coddou, Product Manager, Oracle Data Science; Sherry LaMonica, Consulting Member of Tech Staff, Machine Learning
-* **Last Updated By/Date** - Moitreyee Hazarika, June 2025
+* **Last Updated By/Date** - Moitreyee Hazarika, October 2025

building-blocks/blocks/oml/oml-monitoring/oml-monitoring.md

@@ -170,10 +170,10 @@ To create a data monitor:
 16. Click **Additional Settings** to expand this section and provide advanced settings for your data monitor:
     ![Data monitor - additional settings](images/dm-add-settings.png)
     * **Drift Threshold:** Drift captures the relative change in performance between the baseline data and the new data period. Based on your specific machine learning problem, set the threshold value for your data drift detection. This may require adjusting after you see how your specific data behaves. The default is 0.7. 
-    * **Database Service Level:** This is the Autonomous Database service levels - Low, Medium, High. The default is Low. Service level Medium provides more resources to the data monitor run compared to Low. Service level High provides more resources to the data monitor run compared to Medium.
+    * **Database Service Level:** This is the Autonomous AI Database service levels - Low, Medium, High. The default is Low. Service level Medium provides more resources to the data monitor run compared to Low. Service level High provides more resources to the data monitor run compared to Medium.
     * **Analysis Filter:** Enable this option if you want the data monitoring analysis for a specific time period. Move the slider to the right to enable it, and then select a date in From Date and To Date fields respectively. By default, this field is disabled.
     * **Maximum Number of Runs:** This is the maximum number of times the data monitor can be run according to this schedule. The default is 3. 
-17. The **Features** grid displays the list of features to monitor. Here, you can select or deselect features to include or exclude from monitoring. By default, all features are selected. Feature statistics are provided if the selected data is a table and has RDBMS statistics automatically gathered by Autonomous Database. Oracle Machine Learning Services calculates the statistics on the first run for both, tables and views, and the computations are displayed here after the first run. The statistics are updated by subsequent runs.
+17. The **Features** grid displays the list of features to monitor. Here, you can select or deselect features to include or exclude from monitoring. By default, all features are selected. Feature statistics are provided if the selected data is a table and has RDBMS statistics automatically gathered by Autonomous AI Database. Oracle Machine Learning Services calculates the statistics on the first run for both, tables and views, and the computations are displayed here after the first run. The statistics are updated by subsequent runs.
 ![Data monitor - Features](images/dm-features-grid.png)
 18.Now scroll up to the page and on the top right corner, click **Save.** This completes the task of creating a data monitor and takes you to the Data Monitors page. 
 
@@ -479,8 +479,8 @@ You may now **proceed to the next lab.**
 
 ## Acknowledgements
 
-* **Author** : Moitreyee Hazarika, Principal User Assistance Developer, Database User Assistance Development
+* **Author** : Moitreyee Hazarika, Consulting User Assistance Developer, Database User Assistance Development
 
 * **Contributors:** Mark Hornick, Sr. Director, Data Science / Machine Learning PM; Marcos Arancibia Coddou, Product Manager, Oracle Data Science; Sherry LaMonica, Consulting Member of Tech Staff, Machine Learning
 
-* **Last Updated By/Date**: Moitreyee Hazarika, June 2025
+* **Last Updated By/Date**: Moitreyee Hazarika, October 2025

building-blocks/blocks/oml/oml-nb-visualizations/oml-nb-visualizations.md

@@ -464,6 +464,6 @@ A box plot provides an overview of data distributions in numeric data. It provid
 
 ## Acknowledgements
 
-* **Author** -  Moitreyee Hazarika, Principal User Assistance Developer, Database User Assistance Development
+* **Author** -  Moitreyee Hazarika, Consulting User Assistance Developer, Database User Assistance Development
 * **Contributors** -   Mark Hornick, Senior Director, Data Science and Machine Learning; Marcos Arancibia Coddou, Product Manager, Oracle Data Science; Sherry LaMonica, Consulting Member of Tech Staff, Machine Learning
-* **Last Updated By/Date** - Moitreyee Hazarika, June 2025
+* **Last Updated By/Date** - Moitreyee Hazarika, October 2025

building-blocks/blocks/oml/oml-notebooks-ea/oml-notebooks-ea.md

@@ -41,7 +41,7 @@ This lab assumes you have:
 
 <if type="freetier">
 
-You can access Oracle Machine Learning User Interface from Autonomous Database. Oracle Machine Learning User Interface provides you the following functionalities: 
+You can access Oracle Machine Learning User Interface from Autonomous AI Database. Oracle Machine Learning User Interface provides you the following functionalities: 
 
 * Notebooks - A web-based interface for data analysis, data discovery, data visualization, and collaboration
 * AutoML UI - An interface for no-code automated machine learning modeling and model deployment
@@ -51,7 +51,7 @@ You can access Oracle Machine Learning User Interface from Autonomous Database.
 * Jobs - An interface to create jobs to schedule your notebooks
 
 
-Sign in to Oracle Machine Learning User Interface. Follow the steps in *Task 3 Sign into Oracle Machine Learning User Interface* in the lab _Provision an Autonomous Database with OMLUSERS_ 
+Sign in to Oracle Machine Learning User Interface. Follow the steps in *Task 3 Sign into Oracle Machine Learning User Interface* in the lab _Provision an Autonomous AI Database with OMLUSERS_ 
 
 </if>
 
@@ -251,7 +251,7 @@ Let’s create another paragraph to call the Python interpreter and run Python s
 
 This completes the task of connecting to the Python interpreter and running Python commands in your notebook.
 ### Task 3.5: Use the R Interpreter and run R Statements
-Oracle Machine Learning for R (OML4R) makes the open source R scripting language and environment ready for the enterprise and big data. OML4R integrates R with Oracle Autonomous Database. It allows you to run R commands and scripts for statistical, machine learning, and visualization analyses on database tables and views using R syntax.
+Oracle Machine Learning for R (OML4R) makes the open source R scripting language and environment ready for the enterprise and big data. OML4R integrates R with Oracle Autonomous AI Database. It allows you to run R commands and scripts for statistical, machine learning, and visualization analyses on database tables and views using R syntax.
 
 In this task, you will use the R interpreter and run R statements:
 
@@ -528,6 +528,6 @@ You may now **proceed to the next lab**.
 
 ## Acknowledgements
 
-* **Author** -  Moitreyee Hazarika, Principal User Assistance Developer, Database User Assistance Development
+* **Author** -  Moitreyee Hazarika, Consulting User Assistance Developer, Database User Assistance Development
 * **Contributors** -   Mark Hornick, Senior Director, Data Science and Machine Learning; Marcos Arancibia Coddou, Product Manager, Oracle Data Science; Sherry LaMonica, Consulting Member of Tech Staff, Machine Learning
-* **Last Updated By/Date** - Moitreyee Hazarika, June 2025
+* **Last Updated By/Date** - Moitreyee Hazarika, October 2025

building-blocks/tasks/oml/access-notebook-ea.md

@@ -5,7 +5,7 @@
     }
 -->
 
-A notebook is a web-based interface for data analysis, data discovery, data visualization, and collaboration. You create and run notebooks in Oracle Machine Learning user interface. You can access Oracle Machine Learning user interface from Autonomous Database.
+A notebook is a web-based interface for data analysis, data discovery, data visualization, and collaboration. You create and run notebooks in Oracle Machine Learning user interface. You can access Oracle Machine Learning user interface from Autonomous AI Database.
 
 1. On your Oracle ADW instance, click **Database Actions**.
 

building-blocks/tasks/oml/create-oml-user.md

@@ -11,15 +11,15 @@ An administrator creates a new user account and user credentials for Oracle Mach
 
 To create a user account:
 
-1. If you are not already signed in, sign into your OCI account, click the cloud menu on the left to open the left navigation pane, and click **Oracle Database**. On the right, click **Autonomous Database**.
+1. If you are not already signed in, sign into your OCI account, click the cloud menu on the left to open the left navigation pane, and click **Oracle Database**. On the right, click **Autonomous AI Database**.
 
-	![Autonomous Database under Oracle Database](images/database-adw-rw.png " ")
+	![Autonomous AI Database under Oracle Database](images/database-adw-rw.png " ")
 
-2. The Autonomous Databases dashboard lists all the databases that are provisioned in the tenancy. Click the Oracle Autonomous Database that you have provisioned for this workshop. Here, click the instance **OMLLABS**.
+2. The Autonomous AI Databases dashboard lists all the databases that are provisioned in the tenancy. Click the Oracle Autonomous AI Database that you have provisioned for this workshop. Here, click the instance **OMLLABS**.
 
 	![Oracle Autonomous Data Warehouse](images/adw-omllabs-listed-rw.png " ")
 
-3. On the Autonomous Database details page, click **Database Actions**, and then select the **Database Users** option.
+3. On the Autonomous AI Database details page, click **Database Actions**, and then select the **Database Users** option.
 
 	![Database Actions button in ADB Console](images/database-actions-dbusers-rw.png " ")