Computational Statistics with Python Webinar Video

In this course, we will extend beyond the methods of classical statistics and gain familiarity with contemporary methods for statistical inference driven by computational power. Students will gain experience with the general concepts behind Monte Carlo sampling, Bootstrapping, and Bayesian inference so that these methods may be applied to new problems.

After this course, students will have a conceptual understanding of contemporary statistical methods, as well as hands on experience implementing these methods from scratch on example problems. With this knowledge, students will be prepared to apply these methods to their own problems. 

The video also contains links to the Github repository for the course, which contains a copy of all code and slides.