Degree Plan

B.S. Computer Science & Engineering

120-semester-credit-hour degree plan for the Bachelor of Science in Computer Science & Engineering at Education Redefined Inc.

Effective January 1, 2027 · Last updated September 11, 2026

Program Overview

The Bachelor of Science in Computer Science & Engineering (CSE) is a 120 semester credit hour (SCH) online program delivered asynchronously.

Primary CIP alignment: 11.0701 — Computer Science. Program code: CSE-BS-001. Engineering in this program refers to software systems engineering practice (requirements, testing, security, deployment, and operations).

This is an academic degree in computer science and computing technologies; it does not constitute professional engineering licensure or a licensed Professional Engineer (PE) credential.

A year runs Spring, Summer, Fall. Students complete general education and a common core through Semester 5, then select one track in Semesters 6–8: Computer Science, AI/ML Engineering, or Cybersecurity Engineering.

Prerequisites must be satisfied before enrollment. The semester outline below is a recommended sequence; students may customize pacing when prerequisite requirements are met.

Course materials are provided digitally (OER-first where available). Expand each course for prerequisites and skills students will obtain.

Program Structure

General Education: 33 SCH
Common Core (Semesters 1–5, pre-track): 42 SCH
Work-Based Learning / Capstone Studio (Years 1–3, common to all tracks): 9 SCH, recommended as the last term of the year
Upper-Division Track (Semesters 6–8, one track only): 36 SCH
Total: 120 SCH (33 + 42 + 9 + 36)
Minimum grade for degree progress: D (60%) unless a course specifies a higher competency minimum.

Common Core (Semesters 1–5)

Spring, Year 1 — 15 SCH

UNIV 100 · 3 SCH
Learning Strategies & Academic Integrity in an AI-Enabled Environment
Prerequisites & skills
Prerequisites: None
Skills: Apply evidence-based learning strategies and disclose AI-tool usage transparently in academic work.
COMM 105 · 3 SCH
Professional Communication & Human Skills
Prerequisites & skills
Prerequisites: None
Skills: Draft and deliver professional business communications tailored to a target audience.
MATH 105 · 3 SCH
Calculus & Linear Algebra I
Prerequisites & skills
Prerequisites: None
Skills: Apply differential/integral calculus and linear algebra techniques to solve engineering and data problems.
CSE 101 · 3 SCH
Programming Foundations

Concentration Tracks (Semesters 6–8)

Starting in Semester 6, students complete exactly one track through graduation.

Track A — Computer Science

Summer, Year 3 — 12 SCH

CSE 340 · 3 SCH
Computer Organization & Architecture
Prerequisites & skills
Prerequisites: CSE 330
Skills: Explain computer architecture fundamentals and apply performance-profiling techniques to optimize program execution.
CSE 350 · 3 SCH
Distributed Database Systems
Prerequisites & skills
Prerequisites: CSE 125
Skills: Design and query a distributed/columnar database system and evaluate consistency/performance trade-offs.
CSE 360 · 3 SCH
Theory of Computation
Prerequisites & skills
Prerequisites: CSE 235
Skills: Formally model computation using automata and formal-language theory and reason about decidability/complexity.

Occupations

Training is designed to prepare graduates for entry-level roles including:

Software Engineer (entry-level)
Full-Stack Developer (entry-level)
Web Developer (entry-level)
Cloud Engineer (entry-level)
Junior Data Engineer / ML Engineer (track-dependent)
Junior SOC Analyst / Security Engineer (track-dependent)
Site Reliability Engineer (entry-level)
Cloud Operations Engineer (entry-level)
DevOps Engineer (entry-level)
Backend Software Engineer (entry-level)
Frontend Software Engineer (entry-level)
QA / Test Automation Engineer (entry-level)
Junior Network Engineer (entry-level; track-dependent)
Junior Security Engineer (entry-level; track-dependent)
Junior Application Security (AppSec) Analyst (entry-level; track-dependent)
Junior Incident Response Analyst (entry-level; track-dependent)
Junior AI/ML Engineer (entry-level; track-dependent)
Junior MLOps Engineer (entry-level; track-dependent)

Primary Job Skills

Software engineering

Implement software components and services that satisfy stated requirements.
Build automated tests and produce verification evidence.
Document system behavior, assumptions, and operational procedures.

Full-stack development

Implement user-facing applications and service APIs with secure implementation practices.
Validate input, handle error states, and deliver deployable application artifacts.

Data and database engineering

Model data, write correct SQL queries, and implement reliable data workflows.
Validate data quality and document reproducible query-based evidence.

Cloud, DevOps, and operations

Deploy and operate services using CI/CD and infrastructure-as-code practices.
Implement baseline observability and use logs/metrics to diagnose operational issues.
Build and operate Linux-based systems and containerized services.

Quality engineering

Design and implement automated test suites for functional correctness.
Use CI quality gates and test evidence to prevent and remediate defects.

Security engineering

Career Pathways

Graduates are prepared for roles including:

Software Engineer
Full-Stack Developer
Cloud / DevOps Engineer
Data Engineer
Machine Learning Engineer
AI/LLM Application Engineer
Cybersecurity Analyst
Security Engineer
Quality / Test Engineer
Technical Product Specialist

Faculty Roster

Instructional faculty for the B.S. Computer Science & Engineering program, with academic credentials, specialized training, and assigned courses. Each name links to the faculty member's public profile.

Khuong Le-Nguyen

Faculty

Degree(s) held

Ph.D., Management, Royal Holloway, University of London, UK, 2010. M.Sc., Management, University of Warwick, UK, 2004. Bachelor of Civil Engineering (minor in Project Management), Vietnam National University, Ho Chi Minh City, 1998.

Specialized training

Certificates: MIT (Big Data), Wharton (Business Analytics), Microsoft (Power BI), all 2015; Royal Holloway teaching certificate (2008). Fellow, UK Higher Education Academy. University teaching since 2004 in information systems, databases, and analytics.

Course(s) assigned

Saif Samer Elsaady

Faculty

Degree(s) held

M.S.E., Electrical Engineering, Arizona State University. M.S., Computational Life Science (Data Science), Arizona State University. B.S.E., Electrical Systems Engineering, Arizona State University. B.S., Data Science (Mathematics), Arizona State University, minor in Mathematics.

Specialized training

Doctoral candidate, Ph.D. Electrical Engineering, Arizona State University, expected May 2027. Teaching assistant and grader, Arizona State University (2022–present), supporting 20+ STEM courses. Machine Learning in Python (Udemy); Intel AI Foundations. Graduate engineer, Intel (2024–2025), AI/ML.

Course(s) assigned

Micheal Olaolu Arowolo

Faculty

Degree(s) held

Ph.D., Computer Science, Landmark University, Nigeria, 2021. M.Sc., Computer Science, Kwara State University, Nigeria, 2017. B.Sc., Computer Science, Al-Hikmah University, Nigeria, 2012.

Specialized training

Post-doctoral research scholar, University of Missouri (2022–2024). Oracle Database SQL Certified Expert. Cisco CCNA training. University teaching since 2018 in computer science and AI; Assistant Professor, Xavier University of Louisiana (2024–present).

Course(s) assigned

Nelson Zange Tsaku

Faculty

Degree(s) held

M.S., Computer Science, Kennesaw State University, Georgia, 2019. B.S., Computer Science, Kennesaw State University, Georgia, 2018.

Specialized training

Udacity Data Scientist and Data Engineer Nanodegrees; Udacity mentor (2018–present). Data and Applied Scientist, Microsoft (2021–present). Doctoral candidate, D.Sc. Computer Science, Colorado Technical University, expected 2027.

Course(s) assigned

Noe Lorona

Faculty

Degree(s) held

Doctor of Management in Information Systems, Colorado Technical University, 2023. Master's in IT Management, National American University, 2019. Bachelor's in Information Technology, National American University, 2017. Associate's in Database Administration, Central Texas College, 2015.

Specialized training

CompTIA Security+, CySA+, PenTest+, Network+, AutoOps+, and others. Lean Six Sigma Green Belt. Adjunct Professor, Southern New Hampshire University (2024–present). Platform engineer, U.S. Army Software Factory (2022–present).

Course(s) assigned

Jerry Barboza

Faculty

Degree(s) held

M.C.S., Computer Science, Arizona State University, 2025. B.S., Computer Science, Southern New Hampshire University, 2023. B.S., Applied Mathematics, University of California, Davis, 2021.

Specialized training

Certifications: Big Data Systems; A.I./Machine Learning; Google Data Analytics; Business Analytics (SNHU). Amazon (2021–present): learning trainer, then data analyst. Math tutor, Santa Ana College (2015–2017).

Course(s) assigned

Donna Mendoza

Faculty

Degree(s) held

Master's degree, Cybersecurity and Leadership, University of Washington, 2015. Bachelor of Applied Science, Computer Information Technology, Western Kentucky University, 2011.

Specialized training

Doctoral student, Business Administration and Management, University of North Texas (began August 2026). IT and network professional since 2006, including U.S. Army and U.S. Navy network roles. Skills: information assurance, WAN, switching and routing (BGP, OSPF).

Course(s) assigned

Michael Allen Wilt

Faculty

Degree(s) held

M.S., Applied Mathematics, California State University, Los Angeles, 2015. B.A., Mathematics (with Single Subject Teaching Credential), Otterbein University, 2010. B.A., German, The Ohio State University, 2006.

Specialized training

Mathematics teacher since 2007 (Head Royce School, 2023–present; The Harker School; Bridges Academy). Adjunct math instructor, Glendale Community College (2017–2019). Teaching associate, California State University, Los Angeles (2013–2015). Curriculum developer.

Course(s) assigned

Prasanna Lakshmi Chelliboyina

Faculty

Degree(s) held

M.S., Data Science, Syracuse University, 2025. Bachelor of Technology (Hons.), National Institute of Technology, India, 2020.

Specialized training

Data scientist since 2019, most recently at Walgreens (2025–present). Applied machine learning, generative AI and LLMs, and MLOps on AWS, Azure, and GCP.

Course(s) assigned

Kumar Padmanabhuni

Faculty

Degree(s) held

M.S., Computer Science, California State University.

Specialized training

CISSP (ISC2); AWS Certified Solutions Architect - Associate; Cisco CCNA; SANS SEC595 (AI/ML for cybersecurity). Enterprise security and cloud architect for federal agencies and commercial enterprises since 2011 (Dell, Tenable, Starlite IT Solutions).

Course(s) assigned

Randy Carlson

Faculty

Degree(s) held

M.S., Management of Technology, University of Minnesota, 2002. B.A., Information Technology Management, Concordia University, St. Paul.

Specialized training

Doctoral coursework completed (all but dissertation), Capella University. CISM (ISACA); PMP. 25 years in IT as project, program, and product manager, including cyber defense at Optum. Taught cybersecurity and technology management at Concordia University, St. Paul for 23 years (graduate, online and hybrid).

Course(s) assigned

Paul Smith

Faculty

Degree(s) held

B.B.A., Accounting (minor in Finance), Pace University.

Specialized training

Master's Certificate in Information Assurance, Southern Methodist University. Certificate in Data Privacy and Technology, Harvard University. Certifications: CISSP, CISA, CISM, CRISC, CPA. Cyber risk, governance, and third-party risk professional for 15+ years (Toyota Motor North America, Citi).

Course(s) assigned

Kristopher R. McCoy

Faculty

Degree(s) held

M.S., Cybersecurity, University of Phoenix. B.S., Information Technology, University of Phoenix.

Specialized training

CompTIA Security+; ISC2 Certified in Cybersecurity; Fortinet Certified Associate Cybersecurity; IBM Quantum-Safe Cryptography. Cybersecurity consultant (2025–present). M.B.A., IT Management, Western Governors University, in progress.

Course(s) assigned

Spring, Year 1 — 15 SCH courses
Code	Course	SCH	Details
UNIV 100	Learning Strategies & Academic Integrity in an AI-Enabled Environment	3	Prerequisites & skills Prerequisites: None Skills: Apply evidence-based learning strategies and disclose AI-tool usage transparently in academic work.
COMM 105	Professional Communication & Human Skills	3	Prerequisites & skills Prerequisites: None Skills: Draft and deliver professional business communications tailored to a target audience.
MATH 105	Calculus & Linear Algebra I	3	Prerequisites & skills Prerequisites: None Skills: Apply differential/integral calculus and linear algebra techniques to solve engineering and data problems.
CSE 101	Programming Foundations	3	Prerequisites & skills Prerequisites: None Skills: Design, write, and test programs implementing core programming constructs and data types.
CSE 110	AI-Augmented Software Development Fundamentals	3	Prerequisites & skills Prerequisites: CSE 101 Skills: Build and deploy a client-side web application using modern JavaScript and AI-assisted development workflows with verification logging.

Summer, Year 1 — 15 SCH courses
Code	Course	SCH	Details
CSE 120	Frontend Software Engineering	3	Prerequisites & skills Prerequisites: CSE 110 Skills: Implement a component-based frontend application with automated UI testing and accessibility checks.
CSE 125	Databases I: Data Modeling & SQL	3	Prerequisites & skills Prerequisites: MATH 105; recommended CSE 110 Skills: Design a normalized relational schema and write SQL queries to create, read, update, and analyze data.
CSE 130	Full-Stack Software Engineering Studio (Integrated Project)	3	Prerequisites & skills Prerequisites: CSE 120, CSE 125

Fall, Year 1 — 3 SCH courses
Code	Course	SCH	Details
CSE 191	Work-Based Learning I (Internship)	3	Prerequisites & skills Prerequisites: Completion of CSE 101, 110, 120, 125, 130, or internship readiness approval Skills: Complete a supervised work-based engineering assignment and produce a portfolio-ready artifact with supervisor or oral-defense evaluation.
CSE 195	Capstone Project Studio I (substitution if internship unavailable)	3	Prerequisites & skills Prerequisites: Completion of CSE 101, 110, 120, 125, 130 Skills: Complete a faculty-supervised capstone project substitute and produce a portfolio-ready artifact with oral-defense evaluation.

Spring, Year 2 — 15 SCH courses
Code	Course	SCH	Details
MATH 220	Discrete Mathematics	3	Prerequisites & skills Prerequisites: MATH 105 Skills: Construct and evaluate mathematical proofs and apply discrete-structure techniques to computing problems.
CSE 230	Data Structures	3	Prerequisites & skills Prerequisites: MATH 220 Skills: Implement and analyze core data structures and select structures appropriate to a problem.
CSE 235	Design & Analysis of Algorithms	3	Prerequisites & skills Prerequisites: CSE 230 Skills: Design algorithms using standard paradigms and analyze their time/space complexity.

Summer, Year 2 — 15 SCH courses
Code	Course	SCH	Details
MATH 230	Probability & Statistics	3	Prerequisites & skills Prerequisites: MATH 105 Skills: Apply probability and statistical inference methods to analyze and interpret data sets.
CSE 240	Machine Learning Fundamentals & Practical Applications	3	Prerequisites & skills Prerequisites: CSE 230, MATH 230 Skills: Train, evaluate, and tune supervised machine-learning models on real datasets.
CSE 245	Deep Learning & NLP Foundations	3	Prerequisites & skills Prerequisites: CSE 240 Skills: Implement and train neural network architectures for deep learning and NLP tasks.

Fall, Year 2 — 3 SCH courses
Code	Course	SCH	Details
CSE 291	Work-Based Learning II (Internship)	3	Prerequisites & skills Prerequisites: Completion of CSE 230, 235, 250, 240, 245, 255, 260, or internship readiness approval Skills: Complete an advanced supervised engineering assignment demonstrating progressive technical responsibility.
CSE 295	Capstone Project Studio II (substitution if internship unavailable)	3	Prerequisites & skills Prerequisites: Completion of CSE 230, 235, 250, 240, 245, 255, 260 Skills: Complete an advanced faculty-supervised capstone substitute demonstrating progressive technical responsibility.

Spring, Year 3 — 15 SCH courses
Code	Course	SCH	Details
PHIL 330	Ethics in AI & Technology	3	Prerequisites & skills Prerequisites: None Skills: Evaluate the ethical, fairness, and governance implications of an AI system using an established framework.
MATH 310	Linear Algebra II & Multivariable Calculus	3	Prerequisites & skills Prerequisites: MATH 105; recommended MATH 230 Skills: Apply linear algebra and multivariable calculus techniques to machine-learning and data-analysis problems.
BUS 320	Business Models & Go-to-Market for Software Products	3	Prerequisites & skills Prerequisites: None

Summer, Year 3 — 12 SCH courses
Code	Course	SCH	Details
CSE 340	Computer Organization & Architecture	3	Prerequisites & skills Prerequisites: CSE 330 Skills: Explain computer architecture fundamentals and apply performance-profiling techniques to optimize program execution.
CSE 350	Distributed Database Systems	3	Prerequisites & skills Prerequisites: CSE 125 Skills: Design and query a distributed/columnar database system and evaluate consistency/performance trade-offs.
CSE 360	Theory of Computation	3	Prerequisites & skills Prerequisites: CSE 235 Skills: Formally model computation using automata and formal-language theory and reason about decidability/complexity.
CSE 380	Computer Networks	3	Prerequisites & skills Prerequisites: CSE 250; recommended CSE 330 Skills: Analyze network traffic and configure/troubleshoot core networking protocols in a lab environment.

Fall, Year 3 — 3 SCH courses
Code	Course	SCH	Details
CSE 391	Work-Based Learning III (Internship)	3	Prerequisites & skills Prerequisites: Completion of CSE 330, CSE 370, and the Semester 6 track sequence, or internship readiness approval Skills: Complete a senior-level supervised engineering assignment with increased technical autonomy.
CSE 395	Capstone Project Studio III (substitution if internship unavailable)	3	Prerequisites & skills Prerequisites: Completion of CSE 330, CSE 370, and the Semester 6 track sequence Skills: Complete a senior-level faculty-supervised capstone substitute with increased technical autonomy.

Spring, Year 4 — 12 SCH courses
Code	Course	SCH	Details
CSE 420	Distributed Systems Engineering	3	Prerequisites & skills Prerequisites: CSE 330; recommended CSE 380 Skills: Benchmark and optimize a distributed system for throughput and latency using load-generation and tracing tools.
CSE 450	System Design & Architecture Studio	3	Prerequisites & skills Prerequisites: CSE 330; recommended CSE 380 Skills: Design a system architecture with defined SLIs/SLOs and produce incident-response runbooks.
CSE 470	Software Testing & Quality Engineering	3	Prerequisites & skills Prerequisites: CSE 130; recommended CSE 235

Summer, Year 4 — 12 SCH courses
Code	Course	SCH	Details
CSE 460	AI-Augmented Software Engineering Life Cycle	3	Prerequisites & skills Prerequisites: CSE 130; recommended CSE 370 Skills: Apply an AI-augmented software engineering lifecycle to ship and roll back a multi-service change safely.
CSE 430	Cryptography & Encryption	3	Prerequisites & skills Prerequisites: MATH 220; CSE 370 recommended Skills: Implement and correctly apply cryptographic primitives and detect common cryptographic misuse.
CSE 425	Data Security & Privacy Engineering	3	Prerequisites & skills Prerequisites: CSE 370 required; CSE 350 and CSE 430 recommended

Summer, Year 3 — 12 SCH courses
Code	Course	SCH	Details
AML 311	Data Engineering I	3	Prerequisites & skills Prerequisites: CSE 125; CSE 230; recommended CSE 240 Skills: Build a data-ingestion and validation pipeline with dataset versioning.
AML 341	Data Engineering II	3	Prerequisites & skills Prerequisites: AML 311; CSE 240 recommended; CSE 260 strongly recommended Skills: Design a reliable, multi-source, lineage-tracked data pipeline addressing schema evolution and failure recovery.
AML 331	MLOps I: Packaging, Serving & Monitoring	3	Prerequisites & skills Prerequisites: CSE 250; CSE 240; recommended AML 311

Code

Course

SCH

Details

AML 311

Data Engineering I

Prerequisites & skills

Prerequisites: CSE 125; CSE 230; recommended CSE 240

Skills: Build a data-ingestion and validation pipeline with dataset versioning.

AML 341

Data Engineering II

Prerequisites & skills

Prerequisites: AML 311; CSE 240 recommended; CSE 260 strongly recommended

Skills: Design a reliable, multi-source, lineage-tracked data pipeline addressing schema evolution and failure recovery.

AML 331

MLOps I: Packaging, Serving & Monitoring

Prerequisites & skills

Prerequisites: CSE 250; CSE 240; recommended AML 311

Fall, Year 3 — 3 SCH courses
Code	Course	SCH	Details
CSE 391	Work-Based Learning III (Internship)	3

Code

Course

SCH

Details

CSE 391

Work-Based Learning III (Internship)

Summer, Year 3 — 12 SCH courses
Code	Course	SCH	Details
CYB 331	Cybersecurity Fundamentals I	3	Prerequisites & skills Prerequisites: CSE 370 recommended Skills: Detect and triage security events using SOC/blue-team tooling and the MITRE ATT&CK framework.
CYB 371	Cybersecurity Fundamentals II	3	Prerequisites & skills Prerequisites: None Skills: Analyze core networking protocols, routing, and traffic fundamentals and configure basic network defenses in a lab environment, in preparation for network-security operations.
CYB 361	Digital Forensics & Incident Response	3	Prerequisites & skills Prerequisites: CYB 331; CSE 370 recommended

Code

Course

SCH

Details

CYB 331

Cybersecurity Fundamentals I

Prerequisites & skills

Prerequisites: CSE 370 recommended

Skills: Detect and triage security events using SOC/blue-team tooling and the MITRE ATT&CK framework.

CYB 371

Cybersecurity Fundamentals II

Prerequisites & skills

Prerequisites: None

Skills: Analyze core networking protocols, routing, and traffic fundamentals and configure basic network defenses in a lab environment, in preparation for network-security operations.

CYB 361

Digital Forensics & Incident Response

Prerequisites & skills

Prerequisites: CYB 331; CSE 370 recommended

Fall, Year 3 — 3 SCH courses
Code	Course	SCH	Details
CSE 391	Work-Based Learning III (Internship)	3

Code

Course

SCH

Details

CSE 391

Work-Based Learning III (Internship)

Code	Course	SCH	Details
AML 431	AI Platform Engineering: GPUs, Cost, Reliability	3	Prerequisites & skills Prerequisites: CSE 250; recommended AML 331 Skills: Provision and manage GPU-based ML infrastructure balancing cost and reliability.
AML 442	Natural Language Processing & LLM Engineering	3	Prerequisites & skills Prerequisites: CSE 245 and CSE 255; recommended AML 331 Skills: Build and evaluate an NLP/LLM engineering pipeline including retrieval and safety filtering.
AML 461	Responsible AI: Safety, Bias, Privacy & Governance	3	Prerequisites & skills Prerequisites: PHIL 330; CSE 240; recommended AML 331 Skills: Audit an ML system for fairness, bias, and privacy risk and produce a model card/datasheet.
AML 496	Senior Capstone I	3	Prerequisites & skills Prerequisites: Senior standing; completion of Track B Semester 6 sequence or equivalent Skills: Propose, plan, and defend the initial baseline artifact of an original AI/ML capstone project.

Code	Course	SCH	Details
AML 472	Reinforcement Learning	3	Prerequisites & skills Prerequisites: CSE 240; CSE 245 recommended Skills: Implement and evaluate a reinforcement-learning agent using a standard RL library.
AML 481	Computer Vision Engineering	3	Prerequisites & skills Prerequisites: CSE 245; recommended AML 331 Skills: Build and evaluate a computer-vision model for a defined recognition/detection task.
AML 451	ML/LLM Evaluation Engineering	3	Prerequisites & skills Prerequisites: MATH 230; CSE 240; recommended AML 331 Skills: Design and execute a rigorous ML/LLM evaluation protocol including subgroup and validity analysis.
AML 498	Senior Capstone II	3	Prerequisites & skills Prerequisites: Completion of Senior Capstone I (AML 496); capstone continuation approval Skills: Complete and defend a final AI/ML capstone deliverable with a full evaluation report.

Code	Course	SCH	Details
CYB 401	Network Security (Network Defense Engineering & Traffic Analysis)	3	Prerequisites & skills Prerequisites: Required: CYB 371; Recommended: CSE 370 Skills: Analyze network traffic to detect and respond to network-based attacks.
CYB 411	Cloud Security & Identity (Cloud Security & Identity Engineering)	3	Prerequisites & skills Prerequisites: CSE 250 (or equivalent cloud/IaC readiness); recommended CYB 401, CSE 370 Skills: Configure cloud IAM, secrets management, and audit logging aligned to security benchmarks.
CYB 421	Secure Software Engineering (Application Security Engineering)	3	Prerequisites & skills Prerequisites: CSE 130; CSE 370; recommended CYB 401 Skills: Apply a secure SDLC (SAST/DAST/dependency scanning) to remediate vulnerabilities before release.
CYB 496	Senior Capstone I	3	Prerequisites & skills Prerequisites: Senior standing; completion of Track C Semester 6 sequence or equivalent Skills: Propose, plan, and defend an initial baseline artifact for an original cybersecurity capstone project.

Code	Course	SCH	Details
CYB 341	Security Architecture & Threat Modeling	3	Prerequisites & skills Prerequisites: CYB 401; CYB 411; recommended CYB 421 Skills: Produce a threat model (e.g., STRIDE) and security architecture for a defined system.
CYB 472	Cybersecurity Analysis & Incident Response	3	Prerequisites & skills Prerequisites: CYB 361; CYB 401 Skills: Lead an incident-response exercise from detection through post-incident review using a SIEM.
CYB 430	Applied Cryptography for Cybersecurity	3	Prerequisites & skills Prerequisites: None Skills: Correctly apply and audit cryptographic implementations for common security protocols.
CYB 498	Senior Capstone II	3	Prerequisites & skills Prerequisites: CYB 496 (approved proposal and instructor sign-off) Skills: Complete and defend a final cybersecurity capstone deliverable with a full evaluation report.

Program Overview

Program Structure

Common Core (Semesters 1–5)

Spring, Year 1 — 15 SCH

Concentration Tracks (Semesters 6–8)

Track A — Computer Science

Summer, Year 3 — 12 SCH

Occupations

Primary Job Skills

Software engineering

Full-stack development

Data and database engineering

Cloud, DevOps, and operations

Quality engineering

Security engineering

Career Pathways

Faculty Roster

Summer, Year 1 — 15 SCH

Fall, Year 1 — 3 SCH

Spring, Year 2 — 15 SCH

Summer, Year 2 — 15 SCH

Fall, Year 2 — 3 SCH

Spring, Year 3 — 15 SCH

Fall, Year 3 — 3 SCH

Spring, Year 4 — 12 SCH

Summer, Year 4 — 12 SCH

Track B — AI/ML Engineering

Summer, Year 3 — 12 SCH

Fall, Year 3 — 3 SCH

Spring, Year 4 — 12 SCH

Summer, Year 4 — 12 SCH

Track C — Cybersecurity Engineering

Summer, Year 3 — 12 SCH

Fall, Year 3 — 3 SCH

Spring, Year 4 — 12 SCH

Summer, Year 4 — 12 SCH

AI/ML engineering (track-dependent)

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