Overview
The Bachelor of Science in Cybersecurity and Artificial Intelligence is a major within the School of Applied Sciences. If you have questions regarding this program, please contact dsu.hawk@dickinsonstate.edu or call 1-800-279-HAWK.
Degree Requirements:
- General Education Courses
- Major Courses
- Electives
Degree available in Bismarck, DSUlive, and online
Student Learning Outcomes
A student successfully completing the above major will be able to:
1. Software & System Design: Design, implement, and maintain software and computing systems using modern programming languages, Object-Oriented Programming paradigms, and development methodologies. Apply structured and modular approaches to problem-solving. (This learning outcome directly addresses Institutional Learning Outcomes IV, V, and VII.)
2. Cybersecurity Implementation: Identify, analyze, and mitigate threats in networks, databases, operating systems, and cloud platforms. Apply security frameworks, defensive techniques, and penetration testing methods. (This learning outcome directly addresses Institutional Learning Outcomes IV, V, and VII.)
3. Cryptography & Secure Communication: Implement and evaluate cryptographic algorithms, secure communication protocols, and data protection measures. Demonstrate ability to secure data at rest, in transit, and during computation. (This learning outcome directly addresses Institutional Learning Outcomes IV, V, and VII.)
4. Network & Cloud Security: Configure, monitor, and secure wired/wireless networks, cloud infrastructures, and virtualized systems. Apply knowledge of firewalls, IDS/IPS, VPNs, container security, and cloud compliance standards. (This learning outcome directly addresses Institutional Learning Outcomes IV, V, and VII.)
5. AI & Machine Learning Applications: Develop, train, and evaluate AI/ML models for real-world applications, including predictive analytics, threat detection, natural language processing, and generative AI solutions. (This learning outcome directly addresses Institutional Learning Outcomes IV, V, VII, and X.)
6. Data Analytics & Visualization: Analyze and interpret structured and unstructured data. Apply statistical methods, data mining techniques, and visualization tools to derive actionable insights. (This learning outcome directly addresses Institutional Learning Outcomes IV, V, and VII.)
7. Research & Capstone Execution: Plan, execute, and document independent research or capstone projects. Conduct literature review, apply appropriate methodologies, and present findings effectively. (This learning outcome directly addresses Institutional Learning Outcomes IV, V, VII and VIII.)
8. Ethical & Legal Compliance: Demonstrate understanding of ethical principles, privacy laws, cybersecurity regulations, and responsible AI practices. Evaluate the societal impact of technical solutions. (This learning outcome directly addresses Institutional Learning Outcomes IV, V, VII, and X.)
9. Critical Thinking and Problem Solving: Apply analytical and creative thinking to identify problems, evaluate solutions, and implement effective strategies in computing, AI, and cybersecurity domains. (This learning outcome directly addresses Institutional Learning Outcomes IV, V, and VII.)
10. Professional & Communication Skills: Communicate technical ideas effectively through reports, presentations, and teamwork. Exhibit leadership, collaboration, and lifelong learning skills in professional contexts. (This learning outcome directly addresses Institutional Learning Outcomes IV, V, VII, VIII, and X.)
Semester Sequence
Full list of required courses, in suggested semester order:
Year One, fall semester:
MATH 107 Pre-Calculus
CSCI 160 Computer Science I
CSCI 182 Data Communications and Computer Networks (new course)
(also Gen Eds: UNIV 100, CSCI 101, ENGL 110) *We are working on future adjustments to CSCI 101/160 so that CSCI majors will not have to take both.
Year One, spring semester:
MATH 208 Discrete Mathematics
CSCI 161 Computer Science II
CSCI 200 Database Software Applications
(also Gen Eds: ENGL 120 and another category)
Year Two, fall semester:
CSCI 221 Fundamentals of Cyber Security and Data Encryption
CSCI 330 (was 430) Operating Systems
MATH 305 Probability and Statistics (counts toward Gen Ed elective)
(also 2 Gen Eds.)
Year Two, spring semester:
CSCI 243 Wireless and Mobile Security (new course)
CSCI 303 Python Programming and Algorithms
CSCI 360 Database Management
(also 2 Gen Eds.)
Year Three, fall semester:
CSCI 364 Web and Cloud Security (new course)
CSCI 389 Network and Security - Applications (new course)
CSCI 420 Data Structures and Algorithm Analysis
(also 1 Gen Ed.)
Year Three, spring semester:
CSCI 301 Software Engineering
CSCI 341 Digital Forensics (new course)
AI 384 Fundamentals of Artificial Intelligence
Elective: any AI/CSCI 300+
(also 1 Gen Ed.)
Year Four, fall semester
AI 425 Data Science with Generative AI (new course)
AI 488 Human-Computer Interaction (new course)
CSCI 471 Software Security and Penetration Testing (new course)
CSCI 486 Ethical and Socially Responsible Technology
CSCI 490 Computer Science Research Seminar I (new course)
Year Four, spring semester
CSCI 485 Machine Learning and Data Mining
CSCI 489 Usable Security and Privacy for Human-Centered Design (new course)
CSCI 491 Computer Science Research Seminar II
Elective: any AI/CSCI 300+
(also 1 Gen Ed.)