diff --git a/README.md b/README.md
index 6fb13a4..3861c62 100644
--- a/README.md
+++ b/README.md
@@ -43,28 +43,21 @@ Using a single node interactively provides opportunities for faster code debuggi
 qsub -I -l select=1:node_type=rome -l walltime=01:00:00
 ```
 
-**Step 2.** Go into the project directory:
+**Step 2.** Activate the Conda environment:
 
 ```bash
-cd <project_directory>/deployment_scripts
+# Load the Conda module
+module load bigdata/conda
+source activate # activates the base environment
+
+# List available Conda environments for verification purposes
+conda env list
+
+# Activate a specific Conda environment.
+conda activate ray_environment # you need to execute `source activate` first, or use `source [ENV_PATH]/bin/activate`
 ```
 
-**Step 3.** Deploy the conda environment to the ram disk:
-
-Change the following line by editing `deploy-env.sh`:
-
-```bash
-export WS_DIR=<workspace_dir>
-```
-
-Then, use the following command to deploy and activate the environment:
-
-```bash
-source deploy-env.sh
-```
-Note: Make sure all permissions are set using `chmod +x`.
-
-**Step 4.** Initialize the Ray cluster.
+**Step 3.** Initialize the Ray cluster.
 
 You can use a Python interpreter to start a local Ray cluster:
 
@@ -74,7 +67,7 @@ import ray
 ray.init()
 ```
 
-**Step 5.** Connect to the dashboard.
+**Step 4.** Connect to the dashboard.
 
 Warning: Do not change the default dashboard host `127.0.0.1` to keep Ray cluster reachable by only you.