Introduction to Q Learning in Python
This free online course introduces students to the concepts of probability and expected reward, progressing to the Q-learning algorithm. It is designed for high school students with basic coding knowledge, covering essential programming constructs such as variables, conditionals, loops, and functions. The course is structured as a Jupyter notebook that runs in the browser, making it accessible and interactive. Key features include:
- Hands-on Learning: Students will apply Q-learning to practical scenarios like maze solving and playing tic-tac-toe.
- Clear Explanations: The course offers logical development of topics, ensuring students grasp the concepts without being overwhelmed by complex Python syntax.
- No Advanced Math Required: The course is designed for students who have completed Algebra 2, making it suitable for a wide audience.
This course is an excellent resource for educators looking to introduce machine learning and reinforcement learning concepts in a classroom setting.