
Introduction to Machine Learning
Ended Aug 16, 2022
12 credits
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Full course description
Term: Summer 2022
Date: August 15th & 16th, 2022
Time: 9:00am - 3:00pm both days
Location: Umall 2104 (Directions link)
Instructors: Kate Miller, Jennifer Van Mullekom, & Frances McCarty
Presented By: Statistical Applications and Innovations Group (SAIG)
Description:
Machine learning and data science methods have recently been co-opted into virtually all fields of study. These methods have become an integral part of the toolkit of tomorrow’s worker. Even if you’re not studying statistics, computer science or math, we can guarantee that these tools will be useful for whatever endeavor you plan to undertake in today’s modern economy. In this short course, we will go through an introduction of machine learning methods, both introducing the fundamental concepts underlying the most popular algorithms and showing how to employ these methods to derive meaningful conclusions from data. This course includes both hands-on, in-class exercises and take-home practice exercises for students to sharpen their understanding of the course material. Material is provided in both R and Python.