# STA 4273 Winter 2021: Minimizing Expectations

## Course Introduction

- **University**: University of Toronto
- **Prerequisites**: Bayesian Inference, Reinforcement Learning
- **Course Difficulty**: 🌟🌟🌟🌟🌟🌟🌟
- **Course Website**: [STA 4273 Winter 2021](https://www.cs.toronto.edu/~cmaddis/courses/sta4273_w21/)

"Minimizing Expectations" is an advanced Ph.D. level research course, focusing on the interplay between inference and control. The course is taught by Chris Maddison, a founding member of AlphaGo and a NeurIPS 2014 best paper awardee.

This course is notably challenging and is designed for students who have a strong background in Bayesian Inference and Reinforcement Learning. The curriculum explores deep theoretical concepts and their practical applications in the fields of machine learning and artificial intelligence.

Chris Maddison's expertise and his significant contributions to the field, particularly in the development of AlphaGo, make this course highly prestigious and insightful for Ph.D. students and researchers looking to deepen their understanding of inference and control in advanced machine learning contexts. The course website provides valuable resources for anyone interested in this specialized area of study.