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Final update Unit 0 and 1 with feedback

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simoninithomas
2022-12-05 01:41:15 +01:00
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units/en/unit0/introduction.mdx
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- *To get a certificate of completion*: you need to complete 80% 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.**
## How to get most of the course? [[advice]]
To get most of the course, we have some advice:

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units/en/unit1/additional-readings.mdx
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# Additional Readings [[additional-readings]]
These are **optional readings** if you want to go deeper.
## Deep Reinforcement Learning [[deep-rl]]
- [Reinforcement Learning: An Introduction, Richard Sutton and Andrew G. Barto Chapter 1, 2 and 3](http://incompleteideas.net/book/RLbook2020.pdf)

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units/en/unit1/quiz.mdx
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Congrats on finishing this Quiz 🥳, if you missed some elements, take time to read again the chapter to reinforce (😏) your knowledge.
Congrats on finishing this Quiz 🥳, if you missed some elements, take time to read again the chapter to reinforce (😏) your knowledge, but **do not worry**: during the course we'll go over again of these concepts, and you'll **reinforce your theoretical knowledge with hands-on**.

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units/en/unit2/additional-readings.mdx
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# Additional Readings [[additional-readings]]
These are **optional readings** if you want to go deeper.
## Monte Carlo and TD Learning [[mc-td]]
To dive deeper on Monte Carlo and Temporal Difference Learning:

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units/en/unit3/additional-readings.mdx
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# Additional Readings [[additional-readings]]
These are **optional readings** if you want to go deeper.
- [Foundations of Deep RL Series, L2 Deep Q-Learning by Pieter Abbeel](https://youtu.be/Psrhxy88zww)
- [Playing Atari with Deep Reinforcement Learning](https://arxiv.org/abs/1312.5602)
- [Double Deep Q-Learning](https://papers.nips.cc/paper/2010/hash/091d584fced301b442654dd8c23b3fc9-Abstract.html)