diff --git a/README.md b/README.md
index da88d49..860b758 100644
--- a/README.md
+++ b/README.md
@@ -1,8 +1,13 @@
 # MLFlow Docker Setup [![Actions Status](https://github.com/Toumash/mlflow-docker/workflows/VerifyDockerCompose/badge.svg)](https://github.com/Toumash/mlflow-docker/actions)
 
-If you want to boot up mlflow project with one-liner - this repo is for you. 
+> If you want to boot up mlflow project with one-liner - this repo is for you. 
+> The only requirement is docker installed on your system and we are going to use Bash on linux/windows.
+
+# 🚀 1-2-3! Setup guide 
+1. Configure `.env` file for your choice. You can put there anything you like, it will be used to configure you services
+2. Run `docker compose up`
+3. Open up http://localhost:5000 for MlFlow, and http://localhost:9001/ to browse your files in S3 artifact store
 
-The only requirement is docker installed on your system and we are going to use Bash on linux/windows.
 
 **👇Video tutorial how to set it up on Microsoft Azure 👇**
 
@@ -15,10 +20,6 @@ The only requirement is docker installed on your system and we are going to use
  - Ready to use bash scripts for python development!
  - Automatically-created s3 buckets
 
-# 🚀 Setup guide 
-1. Configure `.env` file for your choice. You can put there anything you like, it will be used to configure you services
-2. Run `docker compose up`
-3. Open up http://localhost:5000 for MlFlow, and http://localhost:9001/ to browse your files in S3 artifact store
 
 ## How to use in ML development in python