Add links Unit 7

README.md

@@ -30,7 +30,7 @@ This course is **self-paced** you can start when you want 🥳.
 | [Published 🥳](https://github.com/huggingface/deep-rl-class/tree/main/unit4#unit-4-an-introduction-to-unity-mlagents-with-hugging-face-) | [🎁 Learn to train your first Unity MLAgent](https://github.com/huggingface/deep-rl-class/tree/main/unit4#unit-4-an-introduction-to-unity-mlagents-with-hugging-face-) | [Train a curious agent to destroy Pyramids 💥](https://colab.research.google.com/github/huggingface/deep-rl-class/blob/main/unit4/unit4.ipynb)  |
 | [Published 🥳](https://github.com/huggingface/deep-rl-class/tree/main/unit5#unit-5-policy-gradient-with-pytorch) | [Policy Gradient with PyTorch](https://huggingface.co/blog/deep-rl-pg)                                     | [Code a Reinforce agent from scratch using PyTorch and train it to play Pong 🎾, CartPole and Pixelcopter 🚁](https://colab.research.google.com/github/huggingface/deep-rl-class/blob/main/unit5/unit5.ipynb)                                       |
 | [Published 🥳](https://github.com/huggingface/deep-rl-class/tree/main/unit6#towards-better-explorations-methods-with-curiosity) | [Towards better explorations methods with Curiosity](https://github.com/huggingface/deep-rl-class/tree/main/unit6#towards-better-explorations-methods-with-curiosity)|                                                                                                         |
-| [Published 🥳]() | Advantage Actor Critic (A2C) | [Train a bipedal walker and a spider to learn to walk using A2C]()                                                                                                        |
+| [Published 🥳](https://github.com/huggingface/deep-rl-class/tree/main/unit7#unit-7-advantage-actor-critic-a2c-using-robotics-simulations-with-pybullet-) | [Advantage Actor Critic (A2C)](https://github.com/huggingface/deep-rl-class/tree/main/unit7#unit-7-advantage-actor-critic-a2c-using-robotics-simulations-with-pybullet-) | [Train a bipedal walker and a spider to learn to walk using A2C](https://github.com/huggingface/deep-rl-class/tree/main/unit7#unit-7-advantage-actor-critic-a2c-using-robotics-simulations-with-pybullet-)                                                                                                        |
 | August the 5th | Proximal Policy Optimization (PPO)                       | 🏗️                                                                                                        |
 | August | Decision Transformers and offline Reinforcement Learning | 🏗️                                                                                                        |