CIS 17A
Introduction to Machine Learning

Course Description

This course introduces the core principles, algorithms, and applications of machine learning. Through hands-on projects in supervised and unsupervised learning, students apply machine learning models to analyze real-world data and then evaluate and improve the accuracy of these models. Students will gain experience with the data preparation workflow, statistical learning, and model selection.

Class Details

CRN Course Section Days Times Instructor Loc
50074 CIS 17A 01Y Seats open Tuesday, Thursday 04:00 PM-05:50 PM Clare Nguyen AT204
No set days TBA-TBA ONLINE

Class Dates: This class runs from 2027-04-05 to 2027-06-25.
Footnote:
CIS-17A.-01Y: HYBRID, meets on-campus and online. This class meets each week on campus and online as noted in the class listing. Students must have access to a computer, the internet and an individual email address. Most De Anza classes will use the Canvas course management system. We recommend a laptop or desktop computer to successfully complete the course; a tablet or phone may not be adequate for all assignments and tests. Information about Canvas and Online Education Orientation can be found in Canvas on the Student Resources page: https://deanza.instructure.com/courses/3382. The Student Online Resources hub with extensive information and tips can be found at deanza.edu/online-ed/students/remotelearning.

Class Materials

View textbook and/or other materials at the Bookstore

Course Details

Units
4.5 Units
Hours
  • Weekly Lecture Hours: 4
  • Weekly Lab Hours: 1.5
Program Status
Program Applicable
Credit
Credit - Degree Applicable
Grading Method
  • Letter Grade
  • Pass/No Pass

Requisite and Advisory

Prerequisite
(CIS 7 and STAT C1000 (or STAT C1000H)) or CIS 11
Advisory
  • CIS 40
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