IT- Information Technology

RE- In this Computer Science course, students will learn about and practice using the tools that developers use on a daily basis such as the debugger, command line, version control systems, and other collaboration tools. Students are also introduced to software testing, writing test cases, and the test-driven development process.

E- This computer science course introduces students to the design and analysis of data structures and algorithms. Students will learn to perform formal asymptotic analysis and to evaluate the efficiency of algorithms. They will compare and contrast multiple implementations of the list, deque, set, map, and priority queue interfaces, including those based on arrays, linked lists, trees, hashing, and heaps. The course also covers fundamental searching and sorting algorithms.

In this computer science course students will gain practical experience in object-oriented programming.  They will apply elementary data structures and algorithms to medium-scale applications. Students gain exposure to fundamental computing theory, including grammars, languages, automata, and major results in computability and complexity theory. Emphasis is placed on collaborative problem-solving, effective version control, memory management techniques, and command-line proficiency. 

In this computer science course, students explore foundational concepts of discrete mathematics and their applications within computing. Students develop the reasoning and problem-solving skills needed for formal logic, mathematical proofs, number theory, and set theory. Through these topics, they learn to analyze and solve problems that underpin advanced areas of computer science, including cryptography, data structures, and algorithm design.

In this computer science course, students extend the foundational concepts developed in Discrete Structures 1 I and apply them to more advanced forms of mathematical reasoning. Students strengthen their ability to construct and analyze mathematical proofs. Building on these skills, the course introduces core topics in the theory of computation, including regular expressions, context-free grammars, and finite automata. Students analyze the expressive power and limitations of these computational models, exploring concepts such as nondeterminism, irregular languages, uncountability, and the Halting Problem.

In this computer science course, students deepen their understanding of data structures and algorithms by focusing on real-world applications drawn from graph theory. Topics include undirected and directed graphs, graph traversals, minimum spanning trees, and shortest-path algorithms. Students will also explore core algorithmic strategies such as divide & conquer, dynamic programming, and problem reductions, as well as concepts related to NP-complete problems and undecidable problems. Throughout the course, emphasis is placed on analyzing algorithmic efficiency within practical problem-solving contexts.

This Information Technology (IT) course introduces students to essential software design principles and patterns related to software development and puts them into practice. These include principles of the Object-Oriented Programming paradigm like Single-responsibility and Open/Closed principle, software architectural elements like Representational State Transfer (REST) and multi-threading, as well as software design patterns such as Factory, Decorator, Strategy, and Model-View-Controller (MVC) patterns.
Prerequisite(s): Admission to BS-Computer Science or BAS-Sustainable Practices programs.

In this computer science course students examine a focused area of computer science chosen by the instructor for the term. Students analyze key technical materials, discuss contemporary challenges, and reflect on broader impacts within the field.  Designed to broaden perspective, the seminar encourages intellectual curiosity and engagement with the evolving landscape of the discipline.  A key goal is to prepare students to take a more independent role in making sense of resources in IT-CS 495.  
NOTE: This course can be repeated for credit. 
 

In this computer science course students will explore applications of artificial intelligence technologies, with a focus on recent/modern Artificial Intelligence (AI) topics such as Large Language Models (LLMs). Topics include the history and capabilities of AI, prompt engineering, building chat applications, AI-assisted coding and software development, agentic AI and tool use (including agent swarms), Retrieval-Augmented Generation (RAG) and retrieval systems, domain-specific applications in enterprise/business settings,  domain specific applications in science settings, and ethics, safety, and responsible use of AI.  With the rapid evolution of AI, it is anticipated that other current topics will supplement this list.  Emphasis is placed on creating systems that utilize and apply AI technologies to address real world challenges.

In this computer science course, students will develop practical software skills for programming resource-constrained systems using appropriate languages and techniques. Topics include the embedded programming model, memory layout and static allocation, bit-level data manipulation, I/O, drivers, interrupt-driven programming, communication protocols, cross-compilation and hardware debugging, and an introduction to real-time operating system concepts. Emphasis is placed on developing reliable, resource-efficient software and on building the mental models needed to reason about hardware and software as a unified system.

In this computer science course students examine a focused area of computer science chosen by the instructor for the term. Students analyze key technical materials, discuss contemporary challenges, and reflect on broader impacts within the field.  Designed to broaden perspective, the seminar encourages intellectual curiosity and engagement with the evolving landscape of the discipline.  Students will be expected to take a greater role in researching, explaining, and presenting topics to the rest of the class
NOTE: This course can be repeated for credit.

RE- Virtualization is an innovative implementation for developing network infrastructures. This in-depth course provides hands-on training and practical experience in a wide range of virtualization technologies and platforms. From fundamental concepts to advanced configurations, you will gain the skills needed to deploy, manage, and secure virtualized environments effectively. Students will learn the most prevalent virtualization platforms including Citrix, Microsoft, and VMware technologies in a multi-layered enterprise-level topology. This course is geared toward current virtualization certifications.

RE- Cloud Architecting explores the essentials of constructing IT infrastructure on the cloud platform with an emphasis on Amazon Web Services (AWS). It aims to equip students with the skills needed to effectively harness cloud technology by understanding the services it offers and integrating them into comprehensive cloud-based solutions. 
While architectural approaches may vary across industries, applications, and business scales, this course underscores universal best practices and recommends design patterns to navigate the architecture of efficient IT solutions in the cloud. Through a scenario-driven format, students engage in hands-on exercises to build various infrastructures, developing a practical understanding of cloud architecture. This course is geared towards the AWS Certified Solutions Architect Associate certification.

RE- This course develops practical skills in monitoring, analyzing, and responding to cybersecurity events in modern network environments. Students learn to interpret security data, investigate alerts, analyze network activity, and apply incident response workflows using common industry tools and techniques. By the end of the course, students will be prepared to support cybersecurity operations and incident response in organizational networks. This course is geared toward the Cisco Cybersecurity Associate certification.

RE- Students explore the design and implementation of effective user interfaces for web sites, mobile apps, and computer applications in this Informational Technology (IT) course. Usability testing and advanced web authoring topics are covered as students gain first-hand experience creating interface designs and graphics for a variety of audiences. Emphasis is placed on aesthetics, accessibility, usability, and working effectively in a team setting to meet client objectives and incorporating client feedback into revisions.

E- Students in this Information Technology (IT) course will explore and practice with relational and non-relational databases including cloud-base systems. Topics of study include information design, database concepts, conceptual vs. physical data modeling, SQL vs. NoSQL databases,  design and development.

RE- In IT 297 the student will identify a paid or unpaid internship, volunteer, or employment opportunity that matches both the outcomes of the students program and their interests. Under the guidance of a faculty advisor, the student will develop appropriate learning outcomes, build on their own capabilities, receive stakeholder feedback, and identify areas of needed growth to prepare for a career in their field of Information Technology (IT). This course uses P/ NP grading. Prerequisite(s): Instructor permission.

In this Information Technology (IT) course, students will focus on developing and utilizing both SQL and NoSQL databases to manage persistent data for applications. Students will learn various technologies to deliver highly available and highly performant data including NoSQL database models and database caching, as well as the business case for and tradeoffs between relational vs. non-relational databases in application development.

Most modern mobile applications communicate with a server, whether it’s sending game scores, posting updates, downloading videos, or receiving notifications.  In this Information Technology (IT) course, students will learn how to design and build systems that follow the Representational State Transfer (REST) architectural styles. Students will explore REST design philosophies to build Application Programming Interfaces (APIs) endpoints. Students will also learn how to use Object-Relational Mapping (ORM) techniques and tools to interact with database systems that will support REST applications.