Course Outline of Record

Item	Value
Eff Term	Fall 2026
Curriculum Committee Approval Date	11/14/2025
Top Code	070200 - Computer Information Systems (CTE)
Units	0 Total Units
Hours	27 Total Hours (Lecture Hours 27)
Total Outside of Class Hours	0
Total Student Learning Hours	27
Course Credit Status	Noncredit (N)
Material Fee	No
Basic Skills	Not Basic Skills (N)
Repeatable	Yes; Repeat Limit 99
Open Entry/Open Exit	No
Grading Policy	P/NP/SP Non-Credit (D),  Letter Non-Credit (L)

Course Description

This course introduces the role of artificial intelligence in cybersecurity, focusing on how AI is used to detect threats, analyze anomalies, and automate security tasks. Students will explore real-world examples of AI-enhanced tools such as intrusion detection systems, phishing detection, and behavioral monitoring. This course emphasizes an understanding of how AI supports cybersecurity professionals and the ethical considerations involved in automating digital defense. Not Transferable.

Course Level Student Learning Outcome(s)

1. Describe how AI technologies are used to support cybersecurity operations, including threat detection, behavior analysis, and system monitoring.
2. Identify examples of AI-enabled cybersecurity tools and explain their roles in preventing, detecting, and responding to cyber threats.
3. Discuss the ethical considerations and limitations of using AI in cybersecurity, such as privacy, bias, and decision-making accountability.

Course Objectives

• 1. Define key terms related to the use of artificial intelligence in cybersecurity, such as anomaly detection, behavioral analytics, and threat intelligence.
• 2. Describe how AI models are used to detect patterns and anomalies in network activity and user behavior.
• 3. Identify common AI-powered cybersecurity tools and their functions (e.g., phishing detection, intrusion detection, malware classification).
• 4. Explain how machine learning supports real-time threat detection and automated incident response.
• 5. Discuss the advantages and limitations of using AI for cybersecurity tasks compared to traditional methods.
• 6. Explore case studies of AI applications in cybersecurity across different sectors (e.g., finance, healthcare, government).
• 7. Analyze ethical and operational concerns related to AI in cybersecurity, including false positives, bias, and privacy risks.

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Lecture Content

1. Introduction to AI in Cybersecurity
2. Threat Detection with AI
3. Machine Learning for Malware Classification
4. Phishing Detection and Email Analysis
5. Behavioral Analytics for Insider Threat Detection
6. Automation in Incident Response
7. AI in Security Operations Centers (SOCs)
8. AI in Cloud and Endpoint Security
9. Case Studies in AI for Cyber Defense
10. Ethical Challenges of AI in Cybersecurity
11. Emerging Trends and Future Skills

Method(s) of Instruction

• Enhanced NC Lect (NC1)
• Live Online Enhanced NC Lect (NC9)
• Online Enhanced NC Lect (NC5)

Instructional Techniques

This course will utilize a combination of lecture, system simulators, classroom discussion with student interactions, problem-solving techniques, quizzes, exams, and troubleshooting assignments to achieve the goals and objectives of this course. All instructional methods are consistent across all modalities.

Reading Assignments

Read open educational resource materials, journal articles and corporate reports, news articles, interactive career websites, and privacy policies.

Writing Assignments

Analyze real-world examples of AI applications in cybersecurity, explain how AI supports threat detection and response, and reflect on the ethical and operational challenges of using AI in digital defense.

Out-of-class Assignments

Research current AI tools used in cybersecurity, review case studies on AI-driven threat detection, and complete short written analyses or reflections on how AI enhances or complicates modern security operations.

Methods of Student Evaluation

• Short Quizzes
• Written Assignments
• Projects (Individual/Group)
• Problem Solving Exercises
• Skills Demonstration

Demonstration of Critical Thinking

Evaluate the effectiveness, limitations, and ethical implications of AI-driven cybersecurity tools when analyzing real-world threats and automated defense strategies.

Required Writing, Problem Solving, Skills Demonstration

Analyze cybersecurity scenarios, apply AI concepts to threat detection and response, and articulate ethical considerations in the use of AI for digital defense.

Resources Subscreen

• Open Education Resource: J.J. Sylvia IV. The Data Renaissance: Analyzing the Disciplinary Effects of Big Data, Artificial Intelligence, and Beyond. (September 2025).

Eligible Discipline(s)

• Computer information systems (computer network installation, microcomputer technology, computer applications): Any bachelor’s degree and two years of professional experience, or any associate degree and six years of professional experience.
• Computer service technology: Any bachelor’s degree and two years of professional experience, or any associate degree and six years of professional experience.
• Computer science: Master’s degree in computer science or computer engineering OR bachelor’s degree in either of the above AND master’s degree in mathematics, cybernetics, business administration, accounting or engineering OR bachelor’s degree in engineering AND master’s degree in cybernetics, engineering mathematics, or business administration OR bachelor’s degree in mathematics AND master’s degree in cybernetics, engineering mathematics, or business administration OR bachelor’s degree in any of the above AND a master’s degree in information science, computer information systems, or information systems OR the equivalent. Note: Courses in the use of computer programs for application to a particular discipline may be classified, for the minimum qualification purposes, under the discipline of the application. Master's degree required.