Update jobs.rst, data_science_job.rst, and 2 more files...

Author: qiuosier

docs/source/user_guide/cli/opctl/_template/jobs.rst

@@ -5,14 +5,14 @@ Working with the CLI
 Prerequisite
 ------------
 
-.. include:: jobs_local_prerequisite.rst
+:doc:`Install ADS CLI <../../quickstart>`
 
 Running a Pre Defined Job 
 -------------------------
 
 .. code-block:: shell
 
-    aads opctl run -j <job ocid>
+    ads opctl run -j <job ocid>
 
 Delete Job or Job Run
 ---------------------

docs/source/user_guide/jobs/data_science_job.rst

@@ -1,10 +1,11 @@
 Quick Start
 ***********
 
-.. admonition:: OCI Data Science Policies
+.. admonition:: Prerequisite
 
   Before creating a job, ensure that you have policies configured for Data Science resources.
-  See also: :doc:`policies` and  `About Data Science Policies <https://docs.oracle.com/en-us/iaas/data-science/using/policies.htm>`_.
+
+  See :doc:`policies` and  `About Data Science Policies <https://docs.oracle.com/en-us/iaas/data-science/using/policies.htm>`_.
 
 .. include:: ../jobs/toc_local.rst
 
@@ -79,10 +80,6 @@ to create the job on OCI. To start a job run, you can call the :py:meth:`~ads.jo
 which returns a :py:class:`~ads.jobs.DataScienceJobRun` instance.
 Once the job or job run is created, the job OCID can be accessed through ``job.id`` or ``run.id``.
 
-The :py:meth:`~ads.jobs.DataScienceJobRun.watch` method is useful to monitor the progress of the job run.
-It will stream the logs to terminal and return once the job is finished.
-Logging configurations are required for this method to show logs.
-
 .. code-block:: python
 
   # Create the job on OCI Data Science
@@ -92,7 +89,9 @@ Logging configurations are required for this method to show logs.
   # Stream the job run outputs
   run.watch()
 
-Here is an example of the logs:
+The :py:meth:`~ads.jobs.DataScienceJobRun.watch` method is useful to monitor the progress of the job run.
+It will stream the logs to terminal and return once the job is finished.
+Logging configurations are required for this method to show logs. Here is an example of the logs:
 
 .. code-block:: text
 

docs/source/user_guide/jobs/infra_and_runtime.rst

@@ -113,6 +113,8 @@ If you specify only the log group OCID and no log OCID,
 a new Log resource is automatically created within the log group to store the logs,
 see also `ADS Logging <../logging/logging.html>`_.
 
+With logging configured, you can call :py:meth:`~ads.jobs.DataScienceJobRun.watch` method to stream the logs.
+
 Runtime
 =======
 
@@ -217,10 +219,9 @@ Here are a few more examples:
 Conda Environment
 -----------------
 
-Except for :py:class:`~ads.jobs.ContainerRuntime`,
-all the other runtime options allow you to configure a
+You can configure a
 `Conda Environment <https://docs.oracle.com/en-us/iaas/data-science/using/conda_understand_environments.htm>`_
-for your workload. You can use the slug name to specify a
+for running your workload. You can use the slug name to specify a
 `conda environment provided by the data science service
 <https://docs.oracle.com/en-us/iaas/data-science/using/conda_viewing.htm#conda-dsenvironments>`_.
 For example, to use the TensorFlow conda environment:

docs/source/user_guide/jobs/run_python.rst

@@ -2,7 +2,7 @@ Run a Python Workload
 *********************
 
 The :py:class:`~ads.jobs.PythonRuntime` is designed for running a Python workload.
-You can configure the environment variables, command line arguments and conda environment
+You can configure the environment variables, command line arguments, and conda environment
 as described in :doc:`infra_and_runtime`. This section shows the additional enhancements provided by
 :py:class:`~ads.jobs.PythonRuntime`.