diff --git a/notebooks/unit1/unit1.ipynb b/notebooks/unit1/unit1.ipynb
index 858fe5a..6f5f103 100644
--- a/notebooks/unit1/unit1.ipynb
+++ b/notebooks/unit1/unit1.ipynb
@@ -787,7 +787,7 @@
         "id": "reBhoODwcXfr"
       },
       "source": [
-        "- In my case, I got a mean reward is `200.20 +/- 20.80` after training for 1 million steps, which means that our lunar lander agent is ready to land on the moon 🌛🥳."
+        "- In my case, I got a mean reward of `200.20 +/- 20.80` after training for 1 million steps, which means that our lunar lander agent is ready to land on the moon 🌛🥳."
       ]
     },
     {
diff --git a/units/en/unit1/hands-on.mdx b/units/en/unit1/hands-on.mdx
index 7ef7469..48d08da 100644
--- a/units/en/unit1/hands-on.mdx
+++ b/units/en/unit1/hands-on.mdx
@@ -478,7 +478,7 @@ mean_reward, std_reward = evaluate_policy(model, eval_env, n_eval_episodes=10, d
 print(f"mean_reward={mean_reward:.2f} +/- {std_reward}")
 ```
 
-- In my case, I got a mean reward is `200.20 +/- 20.80` after training for 1 million steps, which means that our lunar lander agent is ready to land on the moon 🌛🥳.
+- In my case, I got a mean reward of `200.20 +/- 20.80` after training for 1 million steps, which means that our lunar lander agent is ready to land on the moon 🌛🥳.
 
 ## Publish our trained model on the Hub 🔥
 Now that we saw we got good results after the training, we can publish our trained model on the hub 🤗 with one line of code.