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SNHUCourse Prerequisites
Tools

IT460Machine Learning

Course Prerequisites ToolSNHU IT460 has 3 direct prerequisites, with 5 courses in its complete prerequisite tree.

Undergraduate · 3 credits

This course will address the computational study of artificial systems that adapt to novel situations, discover patterns from data, and improve performance with practice through popular frameworks for learning, including supervised, reinforcement, and unsupervised learning. Students will examine a state-of-the-art overview of the field, emphasizing the core statistical foundations.

Prerequisite Tree

  • IT145 — Foundation in Application Development
    • CS110 — Fundamentals of Programming
    • IT140 — Introduction to Scripting
  • MAT240 — Applied Statistics
  • MAT243 — Applied Statistics for Science, Technology, Engineering, and Mathematics (STEM)

Interactive Prerequisite Graph

Explore the prerequisite relationships visually. The graph below supplements the crawlable list above.

React Flow

Unofficial — For Informational Purposes Only

This site is unofficial and is intended for informational purposes only. Course requirements, transfer evaluations, catalog rules, and program requirements can change. Always confirm your academic plan with your SNHU advisor for official guidance.