Computer Science

Introduction to Machine Learning

Introduction to Machine Learning
Machine learning models and other mechanisms allowing computers to learn and find knowledge from data.
 Hours3.0 Credit, 3.0 Lecture, 0.0 Lab
 PrerequisitesC S 312 & MATH 215 & STAT 121; or C S 312 & MATH 215 & STAT 201; or C S 312 & STAT 121
 NoteStudents are allowed 1 repeat of each C S undergraduate course (all 100-, 200-, 300- or 400-level courses). This includes all students who received any grade including those who withdraw (receive a "W" grade) from a C S course. Students must wait 1 semester/term before being allowed to take a course they have failed twice. Petitions for exceptions to the policy can be completed at
 TaughtFall, Winter
 ProgramsContaining C S 472
Course Outcomes: 

Use Effective Machine Learning Techniques

You will learn the basic theory and models used in machine learning


You will be able to recognize when machine learning and data mining tools are applicable.


You will be able to plan and execute successful machine learning and data mining projects, including selecting an adequate process for your specific task and avoiding the main machine learning pitfalls.