diff --git a/8-Reinforcement/1-QLearning/README.md b/8-Reinforcement/1-QLearning/README.md
index 86819de0..e2ce8168 100644
--- a/8-Reinforcement/1-QLearning/README.md
+++ b/8-Reinforcement/1-QLearning/README.md
@@ -25,10 +25,6 @@ You can open [the lesson notebook](notebook.ipynb) and walk through this lesson
 
 In this lesson, we will explore the world of **[Peter and the Wolf](https://en.wikipedia.org/wiki/Peter_and_the_Wolf)**, inspired by a musical fairy tale by a Russian composer, [Sergei Prokofiev](https://en.wikipedia.org/wiki/Sergei_Prokofiev). We will use **Reinforcement Learning** to let Peter explore his environment, collect tasty apples and avoid meeting the wolf.
 
-![peter and the wolf](images/peter.png)
-
-> Peter and his friends need to escape the hungry wolf! Image by [Jen Looper](https://twitter.com/jenlooper)
-
 **Reinforcement Learning** (RL) is a learning technique that allows us to learn an optimal behavior of an **agent** in some **environment** by running many experiments. An agent in this environment should have some **goal**, defined by a **reward function**.
 
 ## The environment
diff --git a/8-Reinforcement/README.md b/8-Reinforcement/README.md
index 464f6aeb..c9881eb4 100644
--- a/8-Reinforcement/README.md
+++ b/8-Reinforcement/README.md
@@ -4,9 +4,9 @@ Reinforcement learning, RL, is seen as one of the basic machine learning paradig
 
 Imagine you have a simulated environment, like the stock market for example. What happens if you impose this or that regulation does it have a positive or negative effect? The whole point is being able to change course if something negative happen, so called _negative reinforcement_ or if it's a positive outcome, to keep building on that, so called _positive reinforcement_.
 
-[![Peter and the Wolf](https://img.youtube.com/vi/Fmi5zHg4QSM/0.jpg)](https://www.youtube.com/watch?v=Fmi5zHg4QSM)
+![peter and the wolf](images/peter.png)
 
-> 🎥 Click the image above to listen to Peter and the Wolf by Prokofiev
+> Peter and his friends need to escape the hungry wolf! Image by [Jen Looper](https://twitter.com/jenlooper)
 
 ## Regional topic: Peter and the Wolf (Russia)
 
@@ -15,6 +15,10 @@ Imagine you have a simulated environment, like the stock market for example. Wha
 - **Explore** the surrounding area and build an optimal navigation map
 - **Learn** how to use a skateboard and balance on it, in order to move around faster.
 
+[![Peter and the Wolf](https://img.youtube.com/vi/Fmi5zHg4QSM/0.jpg)](https://www.youtube.com/watch?v=Fmi5zHg4QSM)
+
+> 🎥 Click the image above to listen to Peter and the Wolf by Prokofiev
+
 ## Reinforcement learning
 
 In previous sections, you have seen two examples of machine learning problems:
diff --git a/8-Reinforcement/1-QLearning/images/peter.png b/8-Reinforcement/images/peter.png
similarity index 100%
rename from 8-Reinforcement/1-QLearning/images/peter.png
rename to 8-Reinforcement/images/peter.png