diff --git a/units/en/unit6/hands-on.mdx b/units/en/unit6/hands-on.mdx
index 4938ca1..e90b7ed 100644
--- a/units/en/unit6/hands-on.mdx
+++ b/units/en/unit6/hands-on.mdx
@@ -1,4 +1,4 @@
-# Advantage Actor Critic (A2C) using Robotics Simulations with PyBullet and Panda-Gym 🤖 [[hands-on]]
+# Advantage Actor Critic (A2C) using Robotics Simulations with Panda-Gym 🤖 [[hands-on]]
 
 
       <CourseFloatingBanner classNames="absolute z-10 right-0 top-0"
@@ -14,9 +14,6 @@ Now that you've studied the theory behind Advantage Actor Critic (A2C), **you're
 We're going to use 
 - [panda-gym](https://github.com/qgallouedec/panda-gym)
 
-<img src="https://huggingface.co/datasets/huggingface-deep-rl-course/course-images/resolve/main/en/unit8/environments.gif" alt="Environments"/>
-
-
 To validate this hands-on for the certification process, you need to push your two trained models to the Hub and get the following results:
 
 - `PandaReachDense-v3` get a result of >= -3.5.