CIS 51
Introduction to Prompt Engineering
Course Description
This course is designed to equip students with the skills needed to effectively design, refine, and implement prompts that guide AI model responses to be both factually accurate and practically useful. Students will learn how to craft clear and purposeful prompt sequences tailored to a variety of applications, including text generation, software development, data analysis, and problem-solving. They will also gain an understanding of the iterative process involved in optimizing AI outputs and develop strategies to troubleshoot common prompt-related challenges. In addition, students will explore key prompt patterns, the construction and deployment of AI Agents and Customized GPTs, and techniques such as Retrieval-Augmented Generation (RAG). The course will also address how to identify and mitigate potential risks and misuse associated with direct access to AI systems.
Class Details
| CRN | Course | Section | Days | Times | Instructor | Loc |
|---|---|---|---|---|---|---|
| 28898 | CIS 51 | 01Y | ·T·R··· | 01:30 PM-03:20 PM | Ronald Kleinman | AT311 |
| ······· | TBA-TBA | ONLINE |
Class Dates: This class runs from 2026-09-21 to 2026-12-11.
Footnote:
CIS -51-01Y: HYBRID, meets on-campus and online. The lecture meets each week as noted in the class listing. The laboratory does not have scheduled meetings and can be completed independently each week on the student's own time. 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.ed/students/remotelearning.
Class Materials
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
- Advisory
- CIS D004.