diff --git a/modules/ROOT/pages/index.adoc b/modules/ROOT/pages/index.adoc
index 5863dc7..04eb503 100644
--- a/modules/ROOT/pages/index.adoc
+++ b/modules/ROOT/pages/index.adoc
@@ -21,26 +21,17 @@ The PTL team acknowledges the valuable contributions of the following Red Hat as
 * Max Murakami
 * Ravi Srinivasan
 
-== Classroom Environment
+== Classroom Environment for Red Hat Associates
 
-There are two options, based on whether you are taking this course standalone (just this course), or as part of the full five course learning path where you installed RHOAI on an OpenShift cluster in the second course in the learning path, _Red Hat OpenShift AI Administration_.
+Continue using the https://demo.redhat.com/catalog?search=Red+Hat+OpenShift+Container+Platform+4.13+Workshop&item=babylon-catalog-prod%2Fopenshift-cnv.ocp413-wksp-cnv.prod[Red Hat OpenShift Container Platform 4.13 Workshop] classroom that you provisioned in the _Red Hat OpenShift AI Administration_ course.
 
-=== Option 1: Standalone (RHOAI Pre-installed on OpenShift)
+You are expected to complete the _Red Hat OpenShift AI Administration_ course, where you install and configure a basic RHOAI instance, and then continue with this course.
 
-You will use the https://demo.redhat.com/catalog?search=openshift+data+science&item=babylon-catalog-prod%2Fsandboxes-gpte.ocp4-workshop-rhods-base-aws.prod[Base RHODS on AWS] catalog item in the Red Hat Demo Platform (RHDP) to run the hands on exercises in this course.
+== Classroom Environment for Red Hat Partners
 
-This classroom has a pre-installed version of Red Hat OpenShift Data Science on OpenShift. 
+Red Hat partners should continue to use the Red Hat OpenShift AI cluster provisioned in the _Red Hat OpenShift AI Administration_ course, using the Red Hat Hybrid Cloud Console at https://console.redhat.com/openshift/overview.
 
-=== Option 2: Five Course Learning Path
-
-Continue using the https://demo.redhat.com/catalog?search=Red+Hat+OpenShift+Container+Platform+4.13+Workshop&item=babylon-catalog-prod%2Fopenshift-cnv.ocp413-wksp-cnv.prod[Red Hat OpenShift Container Platform 4.13 Workshop] catalog item from the _Red Hat OpenShift AI Administration_ course.
-
-[TIP]
-====
-To prevent problems when allocating the workbench pods, make sure that your catalog item has been configured with `64Gi` as the worker memory size.
-====
-
-This classroom does *NOT* have RHOAI pre-installed. You are expected to complete the _Red Hat OpenShift AI Administration_ course, where you install and configure a basic RHOAI instance, and then continue with this course.
+You are expected to complete the _Red Hat OpenShift AI Administration_ course, where you install and configure a basic RHOAI instance, and then continue with this course.
 
 == Prerequisites
 
diff --git a/modules/chapter1/pages/section2.adoc b/modules/chapter1/pages/section2.adoc
index 83c4165..d95debe 100644
--- a/modules/chapter1/pages/section2.adoc
+++ b/modules/chapter1/pages/section2.adoc
@@ -19,8 +19,7 @@ $ oc new-project object-datastore
 +
 [source,console]
 ----
-$ curl https://raw.githubusercontent.com/RedHatQuickCourses/rhods-qc-apps/main/4.rhods-deploy/chapter2/minio.yml
-$ oc apply -f ./minio.yml -n object-datastore
+$ oc apply -f https://raw.githubusercontent.com/RedHatQuickCourses/rhods-qc-apps/main/4.rhods-deploy/chapter2/minio.yml -n object-datastore
 ----
 
 . Get the route to the MinIO dashboard.
@@ -87,7 +86,7 @@ To convert from TensorFlow, use the https://github.com/onnx/tensorflow-onnx[tf2o
 +
 image::iris-download.png[iris model download]
 
-. Upload the file `rf_iris.onnx` to a bucket named **models**, with a path **iris** in your S3
+. Upload the file `rf_iris.onnx` to a bucket named **models**, with a path **iris** in your S3. The username is *minio* and the password is *minio123*.
 +
 image::iris-s3-upload.png[iris model s3 upload]
 +