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ISE 383: Data Analytics and Artificial Intelligence

WOTP Industrial SysEngineering · 4 credits · Western on the Peninsulas

This course introduces students to the principles and practices of data analytics, statistical learning, and artificial intelligence. Core topics include intelligent agents, problem-solving with search, probabilistic reasoning, neural networks, supervised learning (regression, classification, tree-based methods), and unsupervised learning (clustering, dimensionality reduction). Emphasis is placed on both the theory and practical implementation of these methods using Python and industry-standard tools. Students gain hands-on experience through practice sessions, assignments, and a team-based project where they design and present an AI-driven solution to a real-world problem. The course emphasizes critical thinking, problem-solving, and applied analytics, ensuring students understand both the limitations and opportunities of modern AI methods.

Offered in 1 of the 26 listed terms (Spring 2027).

Prerequisites

ISE 301 and ISE 310

Prerequisite tree

Each course's own prerequisites, down to the first courses in the chain.

From Banner's catalog for Spring 2027. Banner lists only the requisites it enforces, so check the catalog entry too.

Required by (0)

No course lists it as a prerequisite.

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None listed yet.

Every offering in the listed terms (1 section)

TermSecCRNTypeMeetsInstructorEnrolledDelivery
Spring 202791P23702LectureS 2:00pm-3:50pm · O-BTStaff0/15Hybrid