CSC 5010. AI Ethics and Vocation. (3 Credits)

This course explores the ethical, vocational, and societal responsibilities of computing professionals in an age increasingly shaped by Artificial Intelligence and emerging technologies. Grounded in the Christian doctrine of vocation, students examine how their technical work serves both neighbor and society, integrating faith-informed purpose with professional excellence. Students will analyze case studies in data privacy, surveillance, algorithmic bias, intellectual property, cybersecurity, and sustainability, while also grappling with the profound ethical implications of AI development, such as autonomous decision-making, deepfakes, and the use of generative models. Emphasis is placed on cultivating discernment, responsibility, and servant leadership in technology design, deployment, and policy. Through discussion, reflection, and project work, students learn to apply consistent moral reasoning across complex computing contexts, preparing them to lead with integrity in both industry and research settings.

CSC 5015. Applied Artificial Intelligence. (3 Credits)

Applied Artificial Intelligence presents the concepts of intelligence, both human and machine, and the nature of information, its origin, description, and transmission. This course will offer a practical approach to incorporating artificial intelligence into useful applications. It includes such topics as: face recognition, speech recognition, and robotic construction. The nature of human intelligence and the limits of machine intelligence will be treated from a scientific, philosophical, and computational perspective.

CSC 5025. Cybersecurity. (3 Credits)

This course is a survey and overview of methods available to safeguard the information technology used in an enterprise today. IT systems are increasingly under attack and therefore knowledge of attacks, protection, and counter-measures is important to the IT practitioner. The IT practitioner must comprehend and manage assurance and security measures within the enterprise. Topics include: operational issues, policies and procedures, attacks and related defense measures, risk analysis, backup and recovery, and the security of information.

CSC 5035. Mobile Computer Architecture. (3 Credits)

An advanced course in current trends in Computer Architecture with a specific emphasis put on decisions related to mobile devices that needs to weigh battery life, heat, and performance more critically than traditional computer systems.

CSC 5040. Applied Computer Networking. (3 Credits)

This course is an in‐depth view of data communication and networking, ranging from the primitive historical approaches to the ever changing modern state of the field. It includes principles of network design, using a top‐down approach and focusing on technologies used in the Internet. It will help students learn to design network‐aware applications using sockets, threading, and concurrency. It will help students understand how the Internet works, from the transport layer down to the physical layer. It will help students prepare for future positions in research and development by introducing them to the latest research in Internet technologies. It will help students become better writers by emphasizing written work where possible. It will also help students apply networking technology in ways that can enrich their lives and assist in spreading the Gospel.

CSC 6000. Database Administration. (3 Credits)

This course provides students with solid theoretical and practical knowledge for developing database management systems. Students will plan, design, implement, maintain, and use database management systems and review the use of databases in small and large commercial organizations. The course addresses concepts, database structures, database architecture, understanding user requirements, user views, functions, and evaluation of database management systems. The course focuses on the relational database model, standard SQL language, database structure normalization, conceptual data modeling, and the entity-relationship data model. Students will work with real world applications and databases. Concepts of data integrity, security, privacy, ethical use, and concurrence control are included.

CSC 6200. Advanced Algorithms. (3 Credits)

This is an advanced course in current trends in Problem Solving and Algorithms that builds on our undergraduate courses data structure (CSC 4400) and CS Theory (CSC 4200). This course will look at emerging algorithms across the grand ideas of computer science. As new technologies emerge, new algorithms must be explored to support them.

CSC 6210. Applied Restful APIs and Integrations. (3 Credits)

From eCommerce to data mining, web systems are the primary information repository of 21st century information technology. This course focuses on: web technologies, information architecture, digital media, web design and development, vulnerabilities and social software.

CSC 6220. Language Theory. (3 Credits)

This is an advanced course in current trends of programming language design and implementation. Students will create a modern trends inspired programming language and solve traditional problems using their creation. This course builds on our undergraduate language theory class (CSC 3210).

CSC 6230. Industrial AI Application and Practice. (3 Credits)

This course bridges the gap between AI theory and real-world deployment by immersing students in the practical application of Artificial Intelligence across industrial sectors such as manufacturing, healthcare, logistics, finance, and agriculture. Students will analyze case studies, evaluate deployment architectures, and work with real or simulated datasets to implement AI solutions that meet performance, security, and compliance requirements in enterprise environments. Topics include production-grade model development, MLOps workflows, edge-AI integration, ethical and regulatory considerations, model monitoring and retraining, and the use of APIs and cloud platforms for scalable deployment. Emphasis is placed on building AI systems that are robust, explainable, and aligned with organizational goals. By the end of the course, students will have delivered an AI project proposal and prototype aligned with an industry-specific use case, preparing them for roles in AI consulting, system integration, and applied research.

CSC 6240. Data Acquisition and Management. (3 Credits)

This course provides a comprehensive foundation in acquiring, managing, and preparing data for use in intelligent systems and data-driven applications. Students will explore the full data lifecycle, from sourcing and ingestion to cleaning, transformation, storage, and retrieval within the context of real-world technical and ethical challenges. Topics include web scraping, API integration, database design, data warehousing, ETL pipelines, data governance, and schema evolution. Students will also address data quality assurance, handling unstructured data, version control, and compliance with legal and ethical standards related to privacy and ownership. Special attention is given to managing large-scale, multi-source datasets in AI and machine learning workflows. By the end of the course, students will be able to design robust data infrastructures that supports scalable AI applications.

CSC 6250. Neural Networks and Deep Learning. (3 Credits)

This course offers an in-depth study of neural network architectures and deep learning techniques that power today’s most advanced Artificial Intelligence systems. This course focuses specifically on the mathematical foundations, structural design, and training dynamics of neural networks. Topics include perceptrons, backpropagation, activation functions, optimization algorithms, regularization methods, and loss functions. Students will analyze and implement advanced architectures such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Long Short-Term Memory (LSTM) networks, Transformers, autoencoders, and generative models. The course also covers techniques for improving training performance, reducing overfitting, and interpreting model outputs. Through hands-on coding assignments, students will build and fine-tune deep models on real-world datasets. Emphasis is placed on critical model evaluation, explainability, and preparation for deployment in research and production contexts.

CSC 6260. Natural Language Processing. (3 Credits)

This course explores the computational techniques that enable machines to interpret, generate, and interact with human language. Students will examine both the foundational linguistics and the advanced algorithms that power modern Natural Language Processing (NLP) systems, from rule-based parsing to large-scale transformer models. Topics include text preprocessing, tokenization, word embeddings, part-of-speech tagging, named entity recognition, syntactic parsing, sentiment analysis, and machine translation. The course covers classic models such as Hidden Markov Models (HMMs) and n-gram language models, as well as deep learning-based approaches including Recurrent Neural Networks (RNNs), sequence-to-sequence models, and transformer architectures. Students will apply techniques in real-world scenarios such as chatbots, summarization, text classification, information retrieval, and question answering. Projects emphasize both implementation and evaluation, with attention to ethical concerns such as bias, misinformation, and the responsible use of generative language models.

CSC 6270. Applied Research Practicum. (3 Credits)

This project-based course provides students with the opportunity to apply advanced computing knowledge and skills to real-world challenges through collaboration with faculty-led research initiatives, industry partners, or interdisciplinary teams. Students will engage in the full lifecycle of a substantial computing project while working in a professional, team-oriented environment. Emphasis is placed on producing work that meets professional standards for quality, scalability, security, and usability, while also demonstrating ethical integrity and consideration of societal impact. Throughout the course, students will refine their skills in technical communication, project management, and collaborative problem-solving. Deliverables include regular progress reports, stakeholder presentations, technical documentation, and a final project showcase. Successful completion of this course will equip students with practical experience, a professional portfolio piece, and potential industry connections that may lead to future employment or research opportunities.

CSC 6400. System Administration and Maintenance. (3 Credits)

This course presents concepts and skills the professional system administrator must understand to effectively maintain enterprise information technology. Topics include: operating systems, application packages, administrative activities, and administrative domains.

CSC 6410. Advanced Networking. (3 Credits)

This is an advanced course which focuses on modern trends in computer networking technology. While this course will be related to the other networking course in this curriculum, it takes a different approach. Focus is placed on advanced topics related to emerging computer networking concepts.

CSC 6420. System Analysis and Design. (3 Credits)

Systems Analysis and Design allows students to investigate the theory, practice, and application of systems analysis and design in the context of information technology. This course emphasizes the vital and various roles played by people during the analysis and design of problem-solving systems. Key topics include requirements, acquisition and sourcing, integration, management, quality assurance, organizational context, and architecture. The tools and techniques of systems analysis and design are covered along with the information technology problem-solving model and appropriate documentation. Prototyping, process and data modeling, feasibility and reliability issues, and user interaction are studied. Current state-of-the-art topics in IT are used as illustrative examples. A project relating to a large IT system allows students to implement analysis and design techniques in a realistic setting.

CSC 7050. Internship in IT. (1 Credit)

The internship provides students with an opportunity to gain valuable practical experience under the guidance of a supervisor/mentor in the work setting, as well as a professor in the academic setting. The goal is to integrate practical work experience with the cumulative knowledge and skills obtained during the students' education. It is expected that students will develop personal, professional and additional academic competencies during the internship. In order to accomplish this, students will need to go beyond the common experiences of a normal employee. Study, reasoning, reflection and theoretical and conceptual exploration will be required for students to develop new skills and knowledge to get the most of the internship experience. All students in the Information Technology program are highly encouraged to obtain relevant work experience in the information technology field before graduation