diff --git a/README.md b/README.md
index d5fad60ee617f64464e560e92e42447d545148a0..c15c86aa2ae35b7859d9907592faa3f9199674a0 100644
--- a/README.md
+++ b/README.md
@@ -9,21 +9,19 @@
 
 ## Part 1: 
 
-### Step 1: Create S3 Bucket
+### Step 1: Object storage Creation
 Create an S3 bucket and upload a few PDF files (Detailed steps are provided in the first session).
 
 ### Step 2: Vector Store Creation
-To set up the Vector Store, run the following command:
-`python Create-Vector-DB.py`
+To set up the Vector Store, run the following command: `python Create-Vector-DB.py`
 
 This script performs the following actions:
-* Set up the security policies: Sets up encryption, network, and data access policies for collections starting with "test".
 
+* Set up the security policies: Sets up encryption, network, and data access policies for collections starting with "test".
 * Vector Store Initialization: Creates a vector store named test1, specifically designed for vector search operations.
-
 * Endpoint Retrieval: After the vector store is set up, the script retrieves and displays the store's endpoint for immediate use.
 
-### Step 3: Processing PDF Files
+### Step 3: Vectorizing the PDF Files
 After setting up the S3 bucket and Vector Store, prepare to vectorize the PDF files:
 * In main.py, update the S3 bucket name to the one you created.
 * Update the Vector Store endpoint with the one provided by the setup script.