CS 224R Deep Reinforcement Learning
will be instantiated with examples from domains with high-dimensional state and action spaces, such as robotics, visual navigation, and control. This course is complementary to CS234, which neither being a pre-requisite for the other. In comparison to CS234, this course will have a more applied and
Before you start
- Basic Python familiarity
- Comfort with algebra or calculus basics
- Interest in robotics systems
About this guide
will be instantiated with examples from domains with high-dimensional state and action spaces, such as robotics, visual navigation, and control. This course is complementary to CS234, which neither being a pre-requisite for the other. In comparison to CS234, this course will have a more applied and deep learning focus and an emphasis on use-cases in robotics and language modeling. [...] ### Format:
The course will consist of twice weekly lectures, three homework assignments, an in-class midterm
Common questions
What will I learn in CS 224R Deep Reinforcement Learning?
will be instantiated with examples from domains with high-dimensional state and action spaces, such as robotics, visual navigation, and control. This course is complementary to CS234, which neither being a pre-requisite for the other. In comparison to CS234, this course will have
Is CS 224R Deep Reinforcement Learning free?
HumanoidHub has not verified public pricing for this guide. Open Stanford Online for the current access terms before enrolling.
Do I need any prerequisites?
Recommended prep: Basic Python familiarity; Comfort with algebra or calculus basics; Interest in robotics systems.
How long does it take?
Self-paced (provider defined). Most learners complete this guide in self-directed sessions over a few weeks.
Does it offer a certificate?
This guide does not include a formal certificate. Focus is on the learning material itself.
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