Education
During my time in San Diego, my educational journey has been marked by a strong foundation and diverse experiences. Starting at Palomar Community College and Cuesta College then transfering to California State University San Marcos , where I earned a degree in Management Information Systems. Now, as a graduate student at the University of San Diego studying Cyber Security Engineering, I’m excited to build upon these experiences and deepen my expertise in cybersecurity.
Cyber Security Engineering Classes at the University of San Diego
- CYBR 501 - Introduction to Cybersecurity Concepts and Tools: An introduction to the fundamentals of cybersecurity, including the notion of policy as the definition of security for a system and the concepts of threats, vulnerabilities, and risk. Survey common attacks and mitigations, and the shortcomings of common, contemporary cybersecurity models. Practice aspects of networking, operating systems, and security test tools through computer virtualization and hands-on labs and assembly of a penetration testing Cybersecurity Sandbox with multiple virtual machines.
- CYBR 502 - Cybersecurity Network Defense: An introduction to fundamental concepts of computer network security and defense, including planning, architecture, system design and deployment, risk assessments, and identifying network security threats from a cybersecurity perspective.
- CYBR 503 - Cybersecurity Domain: The course continues to build on the fundamental concepts introduced in CYBR 501 by advancing the investigation of threats, vulnerabilities, and risk. Introducing and applying security risk frameworks to implement security controls and mediate risk. Testing will be conducted in the student’s Cybersecurity Sandbox.
- CYBR 504 - Applied Cryptography: An introduction to core principles of modern cryptography and applied cryptographic methods and systems. It includes description of common cryptographic algorithms, pseudorandom generators and encryption. Applying and assessing cryptographic systems including defense against attacks and vulnerabilities.
- CYBR 506 - Secure System Life Cycle: Introduced to the approaches for building confidence in the ability of a computer system to correctly enforce the security policy at every stage of the system development life cycle.
- CYBR 508 - Secure Network Engineering: Design of secure and sustainable networks. This includes network hardening methods, advanced configurations of security devices such in IPS, and secure Cloud Computing.
- CYBR 510 - Security Test Engineering: Course presents various methodologies for performing testing to ensure a system conforms to security standards by; 1-Creating and configuring test environments based on security requirements; 2- differentiating between functional testing and security testing; and 3- introducing static, dynamic, vulnerability, and penetration testing.
- CYBR 512 - Incident Detection and Handling: Techniques for assuring the continued operation of secure systems in contested environments will be explored. Use of techniques for the detection of, response to, and recovery from security incidents.
- CYBR 514 - Cyber Engineering Research 1: In Research 1, students will be introduced to a multi domain international company that requires cybersecurity support to update and formalize the security of the enterprise. Student will be required to apply knowledge and skills learned throughout the Cybersecurity Engineering curriculum. The class will be provided a virtual environment with the enterprise systems design in place as per the Case study.
- CYBR 516 - Cyber Engineering Research 2: In Research II, students will continue the implementation of the capstone case study introduced in Research I a multi domain international company that requires cybersecurity support to update and formalize the security of the enterprise. Student will be required to apply knowledge and skills learned throughout the Cybersecurity Engineering curriculum. The class will be provided a virtual environment with the enterprise systems design in place as per the Case study.
Management Information Systems Classes at California State University San Marcos
- MIS 304 - Principles of Management Information Systems: Introduction to subjects in management information systems. Includes computer hardware and software, databases, information systems development, and the role of information systems in the organization.
- MIS 320 - MIS Executives Seminar: Exposes students to challenges facing various industries and introduces students to innovative information system solutions to enhance organizational effectiveness through guest speeches and discovery learning.
- MIS 388 - Java Programming: Covers methods for developing solutions to business and system problems using object-oriented techniques. Covers the fundamental elements of object-oriented programming. Students will learn how to use classes and objects, and the Java Library to develop object-oriented business applications.
- MIS 408 - Information Systems for Business Intelligence: Provides an introduction to using Decision Support Systems for business intelligence. Data management, data warehouses and data marts that support reporting and online analytic processing are studied. The use of key performance indicators, dashboards and scorecards for performance management and opportunity assessment are addressed. Text and web mining are discussed, and the applications of selected machine learning techniques, such as decision trees, genetic algorithm and neural network, are illustrated.
- MIS 410 - Web Development and Business Analytics in Python: Introduces popular programming languages and frameworks for Web Development and Business Intelligence Applications. Teaches students basic Python languages and Python tools that are used to develop web sites and solve business intelligence problems.
- MIS 411 - Database Management: Introduction to data modeling, database design, and database administration. Coverage of the relational database model and construction of a database application using a relational database management system.
- MIS 418 - Information Security Management: Explores information security issues in the areas most commonly encountered in the business environment, using real-life situations. Illustrates how information security addresses current legal requirements, technical threats, and social environments. Examines information security history and purpose, legal issues, development and enforcement of policies and standards, risk management, current threats, technologies, and security program implementation.
- MIS 425 - Business Systems Development: Introduces the methodologies that are widely used in Information Systems Development Projects. Discusses both general project management issues/techniques, such as project scheduling and critical path analysis, and methodologies specifically used in business systems development, such as SDLC, Agile approach, etc.
- MIS 426 - Telecommunication and Network Security: Introduces telecommunications and network security issues typically encountered in management. Focuses on network technologies used by the majority of businesses today along with the information security concepts and practices necessary to implement a secure networking environment for an organization’s desktop and data center operations.
- MIS 460 - Artificial Intelligence: Introduces Artificial Intelligence (AI) from a business information systems perspective, addressing business AI systems design and development, core components and technology, workflows, organizational/social interaction, and their business applications. Teaches the latest AI techniques to build intelligent machines that can perceive, learn, reason, and make decisions automatically and autonomously. Explores how AI is used to empower the various aspects of business administration, such as marketing, human resources, customer management, strategic planning. Emphasizes practice, designing, and implementing AI systems for real-world problem solving
- MIS 498 - Independent Study: Prompt Engineering of GPT-Based Large Language Models - Comprehensive research paper on prompt engineering methodologies for optimizing human-AI interactions, with a specific focus on ChatGPT. The paper explores diverse techniques, including prompting with examples, System 1 and System 2 questions, emotion-driven prompts, prompt programming, and prompt patterns. The evaluation results highlight the strengths and considerations of each methodology, emphasizing their impact on precision, adaptability, versatility, and user engagement.