diff --git a/units/en/unit0/introduction.mdx b/units/en/unit0/introduction.mdx
index 3118d0d..aba76dd 100644
--- a/units/en/unit0/introduction.mdx
+++ b/units/en/unit0/introduction.mdx
@@ -23,7 +23,7 @@ In this course, you will:
 
 - 📖 Study Deep Reinforcement Learning in **theory and practice.**
 - 🧑‍💻 Learn to **use famous Deep RL libraries** such as [Stable Baselines3](https://stable-baselines3.readthedocs.io/en/master/), [RL Baselines3 Zoo](https://github.com/DLR-RM/rl-baselines3-zoo), [Sample Factory](https://samplefactory.dev/) and [CleanRL](https://github.com/vwxyzjn/cleanrl).
-- 🤖 **Train agents in unique environments** such as [SnowballFight](https://huggingface.co/spaces/ThomasSimonini/SnowballFight), [Huggy the Doggo 🐶](https://huggingface.co/spaces/ThomasSimonini/Huggy), [MineRL (Minecraft ⛏️)](https://minerl.io/), [VizDoom (Doom)](https://vizdoom.cs.put.edu.pl/) and classical ones such as [Space Invaders](https://www.gymlibrary.dev/environments/atari/) and [PyBullet](https://pybullet.org/wordpress/).
+- 🤖 **Train agents in unique environments** such as [SnowballFight](https://huggingface.co/spaces/ThomasSimonini/SnowballFight), [Huggy the Doggo 🐶](https://huggingface.co/spaces/ThomasSimonini/Huggy), [VizDoom (Doom)](https://vizdoom.cs.put.edu.pl/) and classical ones such as [Space Invaders](https://www.gymlibrary.dev/environments/atari/), [PyBullet](https://pybullet.org/wordpress/) and more.
 - 💾 Share your **trained agents with one line of code to the Hub** and also download powerful agents from the community.
 - 🏆 Participate in challenges where you will **evaluate your agents against other teams. You'll also get to play against the agents you'll train.**
 
@@ -58,7 +58,8 @@ You can choose to follow this course either:
 
 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.**
+
+You don't need to tell us which path you choose. At the end of March, when we will verify the assignments **if you get more than 80% of the assignments done, you'll get a certificate.**
 
 ## The Certification Process [[certification-process]]
 
@@ -92,7 +93,7 @@ You need only 3 things:
 ## What is the publishing schedule? [[publishing-schedule]]
 
 
-We publish **a new unit every Monday** (except Monday, the 26th of December).
+We publish **a new unit every Tuesday**.
 
 <img src="https://huggingface.co/datasets/huggingface-deep-rl-course/course-images/resolve/main/en/communication/schedule1.png" alt="Schedule 1" width="100%"/>
 <img src="https://huggingface.co/datasets/huggingface-deep-rl-course/course-images/resolve/main/en/communication/schedule2.png" alt="Schedule 2" width="100%"/>
@@ -128,7 +129,7 @@ In this new version of the course, you have two types of challenges:
 
 <img src="https://huggingface.co/datasets/huggingface-deep-rl-course/course-images/resolve/main/en/unit0/challenges.jpg" alt="Challenges" width="100%"/>
 
-These AI vs.AI challenges will be announced **later in December**.
+These AI vs.AI challenges will be announced **in January**.
 
 
 ## I found a bug, or I want to improve the course [[contribute]]