CIS 401 Introduction to Machine Learning
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Additional Content
Minimum Grade for Prerequisites
Unless otherwise indicated, a grade of C or higher is required for all prerequisite courses.
Course Description
This course covers critical machine learning algorithms in AI, including classification (perceptrons, SVMs, Gaussian discriminant analysis), regression techniques (linear, logistic, polynomial, ridge, and Lasso), density estimation (MLE), dimensionality reduction (PCA and random projection), and clustering (k-means and hierarchical).
Units: 4
Degree Credit
Grade Option (Letter Grade or Pass/No Pass)
- Lecture hours/semester: 48-54
- Lab hours/semester: 48-54
- Homework hours/semester: 96-108
Prerequisites: CIS 400
Corequisites: None
AA/AS Degree Requirements: Area E2b
Transfer Credit:
CSU
, UC
