I’m excited to be writing this book review. It is a book for which I’ve been waiting a long time. An Introduction to Statistical Learning with Application in R by James, Witten, Hastie, and Tibshirani ...

A course in statistics at the level of IEMS 303; A course in matrix analysis; Proficiency in programming, as extensive coding will be a key part of the curriculum. This course is considered a ...

This course is the starting point for learning about statistical analysis in clinical and public health research. Attendees will learn the key concepts from statisticians working with the many ...

Throughout the week, you will learn how to apply SVMs to classify or predict outcomes in a given dataset, select appropriate kernel functions and parameters, and evaluate model performance. In this ...

*Note: This course description is only applicable for the Computer Science Post-Baccalaureate program. Additionally, students must always refer to course syllabus for the most up to date information.

A substantially revised third edition of a comprehensive textbook that covers a broad range of topics not often included in introductory texts. The goal of machine learning is to program computers to ...

We are not currently accepting applications for this course. Register your interest below to be notified when applications open again. Data Science and Big Data Analytics are exciting new areas that ...

This course is the starting point for learning about statistical analysis in clinical and public health research. Attendees will learn the key concepts from statisticians working with the many ...

In the ever-evolving toolkit of statistical analysis techniques, Bayesian statistics has emerged as a popular and powerful methodology for making decisions from data in the applied sciences. Bayesian ...