Course Description

This course aims to help clinicians develop an understanding of how to frame neurosurgical problems using the best data science approach. The program will provide neurosurgeons and neurosurgical residents with an overview of different machine learning / data science models, coupled with examples of these models in neurosurgical patient populations. The program will include didactic lecture with interactive polling and question and answer sessions, as well as a breakout session for more focused learning in a smaller group.

Industry Support Options

Learning Objectives

Upon completion of this course, participants will be able to:
1. Discuss and analyze the key differences between unsupervised and supervised learning.
2. Compare and evaluate the strengths, weaknesses, and limitations of various data science models.
3. Evaluate whether a hypothesis can be answered using specific models.

Note for Program Coordinators: Register your residents for the Data Science Models for Neurosurgeons Course by using the subscription tool in your Institution account. This purchase option for institutions can ONLY be purchased by a program coordinator to enable the purchase of the course on behalf of someone else. View step-by-step instructions here. (Residents can also register for themselves through the product listing for the Data Science Course.)