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Applications of Machine Learning in Data Analysis

QAC 385
Spring 2019 not offered
Certificates: Applied Data Science
Course Cluster: Data Analysis Minor

The course provides a broad overview of machine learning algorithms and focuses on their application in data mining. Building on a basic background of regression analysis, and following a learning-by-doing approach, students are introduced to data mining tools and techniques that are used to identify patterns and relationships in large and complex data. While the emphasis is on intuition and application rather than theoretical results, through different case studies, students are introduced to the fundamentals of the different methods and learn how to conceptualize a problem, analyze it using appropriate tools, and communicate their results.
Credit: 1 Gen Ed Area Dept: NSM QAC, SBS QAC
Course Format: Laboratory CourseGrading Mode: Graded
Level: UGRD Prerequisites: QAC211 OR [PHYS221 or QAC221 or CIS231] OR ECON300 OR [GOVT367 or QAC302] OR MATH231 OR MATH232
Fulfills a Major Requirement for: (CADS)(DATA-MN)

Last Updated on SEP-30-2023
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