Faculty Syllabus

Approved Course Texts / Readings

There is no book to buy.

All materials will be supplied through Blackboard.

Please follow the required sequences for reading materials.

We will be using the dedicated textbook, custom resources, as well as outside sources such as case studies, videos, podcasts, and more.

Software Requirements

Students must be able and willing to install software and applications independently.

Minimum Computer/Laptop Recommendations

1. Intel i5 processor (i7 preferred)
2. 16 GB RAM (32 GB preferred)
3. 500 GB SSD (NVMe M.2 preferred)

This course can be completed on Mac or Windows systems. Mac users may need additional research to complete some labs.

This course uses a competency-based structure. Students must demonstrate mastery of one competency before advancing to the next.

Orientation and Forced Sequence

• Orientation assessment must be completed with a score of 90 percent or higher to unlock the rest of Comp1 and the Capstone.
• Each competency ends with a required project.
• Projects must be submitted to unlock the next competency.
• The Capstone becomes available after Orientation and should be reviewed early. Do not wait!!
• No late Capstone submissions are accepted.
• Students must mark sections complete in the LMS.

Assessment Attempts

One attempt only for all assessments and checkpoints (quizzes). Students should study carefully before submitting.

Pace and Deadlines

• Students may work ahead.
• Deadlines are firm.
• Missed deadlines cannot be reopened.

Project Submissions and Policies

• Each competency includes a project submission.
• Instructions must be followed exactly.
• Late submissions lose 10 percent per calendar day.
• No submissions accepted after day three.
• Incorrect file formats result in an automatic 20 percent deduction.
• All sources must be cited, including AI tools unless otherwise stated.

📅 Due Dates & Deadlines

All due dates are listed in Blackboard Ultra.

Students are responsible for checking the calendar regularly.

The course allows flexibility, but students cannot fall behind.

Grade Policy

Grades are based on both conceptual understanding and practical application, including assessments, activities, and potential programming assignments.

Assessments

• Each competency includes an assessment.
• Exams are open book.
• Exams must be completed by the due date.
• Exam links close at 11:59 PM Central Time.
• No makeup exams.
• No extra credit.
• Missed exams receive a zero.

Grading Scale

Course Performance Note:

Doing the bare minimum earns at best a C.

Higher grades require higher-quality and more complete work.

Rubrics must be read and followed carefully.

READ the rubrics

Course Requirements

Time Commitment

This is a junior-level course. Students should expect to spend 10 to 12 or more hours per week on coursework.

Reading Assignments

Readings and supplemental materials are required. Skipping materials often leads to poor performance.

Tutorials

Some topics include tutorials that may be included in assessments.

Discussions

Discussion participation may count toward attendance in online sections.

Attendance and Participation

If the college closes due to emergencies, students must continue communication and complete assigned work.

Course Schedule

Schedule changes may occur and will be announced in Blackboard and by email.

Programming Assignments

All assignments must be completed independently and submitted through Blackboard.

Late work loses 10 percent per day. Submissions close four days after the due date.

Withdrawal Policy

Students are responsible for officially withdrawing from the course if needed. Withdrawal deadlines are listed in the academic calendar. The instructor may also withdraw students at their discretion.

COMPETENCY 1 - ORIENTATION, AI, and CYBERCRIME

Understanding ethical and legal AI use is vital in today’s digital world, where bias, misinformation, and privacy risks have real consequences. Responsible AI practices build trust, ensure legal compliance, and prepare students for professional use. This competency also examines how cybercrime cases move through the U.S. legal system—from trial courts to the Supreme Court—highlighting digital evidence, constitutional protections, and laws like the Texas Data Breach Notification Act. Through case studies, students learn ethical hacking responsibilities, judicial escalation, and how to anticipate legal challenges while fostering secure, compliant digital environments.

COMPETENCY 2 - ETHICS, LAWS, & COMPLIANCE

Instead of one central system, agencies like DHS, CISA, and the DOJ share responsibility for protecting networks, responding to threats, and working with private companies. The FTC enforces privacy under Section 5 of the FTC Act through case-by-case actions, meaning businesses must study past rulings to understand what counts as unfair or deceptive. Sector laws like HIPAA and GLBA require stricter safeguards for healthcare and finance, shaping data practices and public trust. By learning how laws and enforcement address evolving threats, students gain the skills to protect information, ensure compliance, and reduce risk for individuals and organizations.

COMPETENCY 3 - MANAGING RISK & COMMUNICATING LEGAL RESPONSIBILITIES

Students will gain an understanding of how constitutional protections, statutory frameworks, and organizational practices shape the field of cyber law. They will explore how the Fourth Amendment applies to modern surveillance and how courts interpret privacy in light of new technologies. Students will distinguish legal boundaries for electronic data collection. Students will also examine debates over encryption, compelled decryption, and constitutional rights. Beyond theory, they will apply risk management strategies, strengthen compliance through policies and documentation, navigate stakeholder dynamics, use the RACI model for accountability, and practice communication protocols ensuring legal protection and audit readiness.

COMPETENCY 4 - GLOBAL AND EMERGING ISSUES

As technology advances, new legal challenges arise, from data privacy and cybersecurity regulations to the ethical implications of emerging technologies like artificial intelligence and blockchain. Understanding these issues equips professionals with the knowledge to navigate complex legal frameworks, ensure compliance, and safeguard digital infrastructure against evolving cyber threats.

CAPSTONE

This course has taken you through the foundations of law, compliance, and technology, from understanding court systems to analyzing privacy laws. You practiced legal reasoning with tools like IRAC and applied compliance checklists to real-world policies. Along the way, we highlighted how stakeholders, ethics, and clear documentation shape legal and organizational decisions. Now, you will bring these skills together in the Capstone, where you will analyze a realistic case and propose clear, practical solutions. This final project will show how far you have come and prepare you for real-world challenges ahead.

Course Description & Rationale

Pre-requisite

• CSIS 3333 or Departmental Approval
• Reading, writing, and basic use of Microsoft Office

Students entering this course should be able to research technical issues, locate reliable information, understand the material they find, and implement basic solutions without step-by-step guidance.

Course Description

This seminar explores the legal system’s response to the rapidly evolving challenges posed by cybercrime. We will examine how courts and legislators are struggling to adapt traditional legal principles to digital misconduct, the role (and limitations) of law enforcement, tensions between security and privacy in the fight against cybercrime, the legal implications of the global reach of cybercrime and the growing threat of state actors, and the impact of government regulation in promoting cybersecurity.

We also will seek to provide students with a basic literacy regarding cybersecurity issues likely to touch nearly every lawyer’s practice. Students will learn about common types of cybercrime and security measures, lawyers’ ethical obligations concerning cybersecurity, and the role of lawyers in helping clients meet their cybersecurity-related legal responsibilities and responding to cybersecurity incidents.

Course Objectives / Learning Outcomes

After completing this course, you should be able to:

• Define law and the structure of the US legal system.
• Distinguish between various types of cyber crime laws.
• Distinguish intellectual property laws, including benefits and limitations.
• Explain the scope and limitations of privacy laws.
• Determine legal behavior versus illegal behavior within the scope of relevant laws.
• Identify privacy concerns and the means to protect one’s privacy.

This class is a junior level class and the expectations are probably higher than some of you have experienced in the past. This class will be challenging and time-intensive, yet I hope when it is done, y’all will agree it was worth it and you are now a stronger competitor for the job you want.

Introduction

In this course, Generative AI (GAI) tools—such as ChatGPT, Copilot, Bard, and similar platforms—can be powerful aids for learning and creativity. I support their responsible, transparent, and ethical use when it enhances understanding and does not replace your own critical thinking or original work. In fact, you will have AI assignments which must be completed before starting other course work.

Used correctly, these tools can help you explore ideas, understand terminology, and see multiple approaches to solving a problem. Used incorrectly, they can hide gaps in understanding and produce work that looks correct but is not. This policy sets clear expectations so you can use these tools in ways that strengthen your skills and protect academic integrity.

Rationale

In the world today, being able to use AI is a must. Even in non-programming roles, the understanding and uses of AI are inescapable and required for all jobs eventually. But to use it correctly, you need to understand what it can do and how it can be used to break things very easily. Imagine GAI as a 6-foot chainsaw that everyone now has. But do you need a 6-foot chainsaw for everything? Use it responsibly.

In technical fields, AI can speed up learning, but it can also amplify mistakes. AI can generate insecure code, misleading explanations, and incorrect citations with high confidence. Learning to verify outputs, recognize limitations, and document your process is part of professional readiness. This course treats AI literacy as a real-world skill that must be practiced with discipline and good judgment.

Definition

For this course, GAI refers to any technology that can generate text, code, images, audio, or other media in response to prompts, including—but not limited to—OpenAI ChatGPT, Google Gemini, GitHub Copilot, DALL·E, and similar AI-driven content creation tools. If you must tell the system what to do, chances are it is AI and falls under this category. Applications like Grammarly and Zotero are great for typos, grammar, and citations BUT they do not always work! Please double check your citation submissions!

This definition includes tools embedded inside editors, browsers, learning platforms, and search engines when they produce generated output rather than simply retrieving sources. If a tool is “suggesting” full sentences, paragraphs, solutions, or code blocks based on prompts or context, it is included. When in doubt, treat the tool as GAI and disclose its use so there is no confusion later.

Resources

• Review the tool’s terms of service and privacy settings.
• Cross-check AI-generated content with authoritative sources.
• Use AI output only as a starting point, not as a final submission, unless noted in assignments and assessments.
• Apply proper citations when AI output informs your work.

For technical topics, “authoritative sources” means official documentation, standards, reputable textbooks, and instructor-provided materials. If AI provides a claim, you should be able to verify it independently. Keep brief notes about what you asked, what you received, what you accepted or rejected, and why. This habit strengthens learning and makes disclosure easy.

Assessment

Unless otherwise noted, all assignments must reflect your own comprehension and skills. AI assistance must be disclosed as a formal APA 7 citation when used. See Resources link for how to use APA 7 properly.

Disclosure is required whether AI helped you generate content, refine wording, produce code, summarize sources, or brainstorm approaches. If AI influenced your final submission in any meaningful way, cite it. Your grade depends on demonstrating your understanding, so you should be prepared to explain and defend your choices, your code, and your reasoning without relying on the tool during grading.

Penalties

Failure to follow this policy—including failure to disclose AI use—will be treated as a violation of the college’s academic integrity policy. Penalties may include a zero for the assignment, additional work, or escalation to the Academic Integrity Committee.

This includes submitting AI-generated work as if it were entirely your own, using AI during restricted activities, or presenting generated output that you do not understand. Penalties may also apply when citations are missing, misleading, or intentionally vague. If you are unsure whether your use requires disclosure, disclose it. Transparency protects you.

Exceptions

Specific assignments may prohibit AI use entirely (e.g., in-class exams) or require it (e.g., AI prompt engineering exercises). Such exceptions will be clearly stated in the assignment instructions.

When AI is prohibited, you must complete the work without AI assistance, including drafting, rewriting, or “checking” your work with a tool. When AI is required, you must follow the stated workflow, including documenting prompts and outputs, and meeting any citation or submission rules. If instructions conflict, the assignment instructions take precedence.

Usage Permissions

Please closely read requirements for all assignments and submissions as they differ from one to the next.

Some tasks will allow AI for brainstorming but not for final wording. Other tasks may allow AI-generated starter code but require you to modify, test, and explain it. In all cases, you are responsible for the final product you submit, including correctness, security, and clarity. If an assignment requires disclosure details, follow that format exactly.