Add certification info in hands-on and introduction

notebooks/unit1/unit1.ipynb

@@ -166,6 +166,20 @@
         "# Let's train our first Deep Reinforcement Learning agent and upload it to the Hub 🚀\n"
       ]
     },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "## Get a certificate\n",
+        "To validate this hands-on for the [certification process](https://huggingface.co/deep-rl-course/en/unit0/introduction#certification-process), you need to push your trained model to the Hub and **get a result of >= 200**.\n",
+        "\n",
+        "To find your result, go to the [leaderboard](https://huggingface.co/spaces/huggingface-projects/Deep-Reinforcement-Learning-Leaderboard) and find your model, **the result = mean_reward - std of reward**\n",
+        "\n",
+        "For more information about the certification process, check this section 👉 https://huggingface.co/deep-rl-course/en/unit0/introduction#certification-process"
+      ],
+      "metadata": {
+        "id": "qDploC3jSH99"
+      }
+    },
     {
       "cell_type": "markdown",
       "source": [

notebooks/unit2/unit2.ipynb

@@ -3,8 +3,7 @@
     {
       "cell_type": "markdown",
       "metadata": {
-        "id": "view-in-github",
-        "colab_type": "text"
+        "id": "view-in-github"
       },
       "source": [
         "<a href=\"https://colab.research.google.com/github/huggingface/deep-rl-class/blob/main/notebooks/unit2/unit2.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
@@ -169,6 +168,20 @@
         "id": "HEtx8Y8MqKfH"
       }
     },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "\n",
+        "To validate this hands-on for the [certification process](https://huggingface.co/deep-rl-course/en/unit0/introduction#certification-process), you need to push your trained Taxi model to the Hub and **get a result of >= 4.5**.\n",
+        "\n",
+        "To find your result, go to the [leaderboard](https://huggingface.co/spaces/huggingface-projects/Deep-Reinforcement-Learning-Leaderboard) and find your model, **the result = mean_reward - std of reward**\n",
+        "\n",
+        "For more information about the certification process, check this section 👉 https://huggingface.co/deep-rl-course/en/unit0/introduction#certification-process"
+      ],
+      "metadata": {
+        "id": "Kdxb1IhzTn0v"
+      }
+    },
     {
       "cell_type": "markdown",
       "source": [
@@ -1734,8 +1747,7 @@
         "Ji_UrI5l2zzn",
         "67OdoKL63eDD",
         "B2_-8b8z5k54"
-      ],
-      "include_colab_link": true
+      ]
     },
     "gpuClass": "standard",
     "kernelspec": {
@@ -1748,4 +1760,4 @@
   },
   "nbformat": 4,
   "nbformat_minor": 0
-}
+}

units/en/unit0/introduction.mdx

@@ -53,12 +53,21 @@ The course is composed of:
 You can choose to follow this course either:
 
 - *To get a certificate of completion*: you need to complete 80% of the assignments before the end of March 2023.
+- *To get a certificate of honors*: you need to complete 100% of the assignments before the end of March 2023.
 - *As a simple audit*: you can participate in all challenges and do assignments if you want, but you have no deadlines.
 
 Both paths **are completely free**.
 Whatever path you choose, we advise you **to follow the recommended pace to enjoy the course and challenges with your fellow classmates.**
 You don't need to tell us which path you choose. At the end of March, when we verify the assignments **if you get more than 80% of the assignments done, you'll get a certificate.**
 
+## The Certification Process [[certification-process]]
+
+The certification process is **completely free**:
+
+- *To get a certificate of completion*: you need to complete 80% of the assignments before the end of March 2023.
+- *To get a certificate of honors*: you need to complete 100% of the assignments before the end of March 2023.
+
+<img src="https://huggingface.co/datasets/huggingface-deep-rl-course/course-images/resolve/main/en/unit0/certification.jpg" alt="Course certification" width="100%"/>
 
 ## How to get most of the course? [[advice]]
 

units/en/unit1/hands-on.mdx

@@ -18,6 +18,12 @@ And finally, you'll **upload this trained agent to the Hugging Face Hub 🤗, a
 
 Thanks to our <a href="https://huggingface.co/spaces/huggingface-projects/Deep-Reinforcement-Learning-Leaderboard">leaderboard</a>, you'll be able to compare your results with other classmates and exchange the best practices to improve your agent's scores. Who will win the challenge for Unit 1 🏆?
 
+To validate this hands-on for the [certification process](https://huggingface.co/deep-rl-course/en/unit0/introduction#certification-process), you need to push your trained model to the Hub and **get a result of >= 200**.
+
+To find your result, go to the [leaderboard](https://huggingface.co/spaces/huggingface-projects/Deep-Reinforcement-Learning-Leaderboard) and find your model, **the result = mean_reward - std of reward**
+
+For more information about the certification process, check this section 👉 https://huggingface.co/deep-rl-course/en/unit0/introduction#certification-process
+
 So let's get started! 🚀
 
 **To start the hands-on click on Open In Colab button** 👇 :

units/en/unit2/hands-on.mdx

@@ -16,6 +16,12 @@ Now that we studied the Q-Learning algorithm, let's implement it from scratch an
 
 Thanks to a [leaderboard](https://huggingface.co/spaces/huggingface-projects/Deep-Reinforcement-Learning-Leaderboard), you'll be able to compare your results with other classmates and exchange the best practices to improve your agent's scores. Who will win the challenge for Unit 2?
 
+To validate this hands-on for the [certification process](https://huggingface.co/deep-rl-course/en/unit0/introduction#certification-process), you need to push your trained Taxi model to the Hub and **get a result of >= 4.5**.
+
+To find your result, go to the [leaderboard](https://huggingface.co/spaces/huggingface-projects/Deep-Reinforcement-Learning-Leaderboard) and find your model, **the result = mean_reward - std of reward**
+
+For more information about the certification process, check this section 👉 https://huggingface.co/deep-rl-course/en/unit0/introduction#certification-process
+
 
 **To start the hands-on click on Open In Colab button** 👇 :