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 |
|---|---|---|---|---|---|---|
| 40033 | CIS 17A | 01Y | ·T·R··· | 04:00 PM-05:50 PM | Clare Nguyen | AT204 |
| ······· | TBA-TBA | ONLINE |
Class Dates: This class runs from 2027-01-04 to 2027-03-26.
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
This course either has not submitted any materials to the bookstore for use or is using Open Education Resources. Please check with the instructor.
View textbook and/or other materials available 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
- Pass/Fail Grading
Requisite and Advisory
- Prerequisite
- (CIS D007. and STAT C1000 (or STAT C1000H)) or CIS D011.
- Advisory
- CIS D040.