CSC - Computer Science Course Descriptions
Is a thorough introduction to computers, including hardware and software concepts. Hands-on experience using micro-computer hardware and software tools is included. Elementary skills in using such computer tools as word processing, spreadsheets, database managers, and programming will be developed as time allows. Social issues involving computers will be discussed.
Serves three main purposes: to develop in students an understanding of the algorithmic formulation of methods for problem solving on a computer; to train students to use at least one procedural computer language; and to acquaint students with the basic properties of computers.
Serves three main purposes: to develop in the students an understanding of the principles of object-oriented programming, to introduce the student to the algorithmic methods for problem solving on the computer, and to train students to use at least one object-oriented computer language.
Introduces data structures such as stacks, queues, lists, trees, and graphs in an object-oriented framework. The material of this course is fundamental in the object-oriented analysis and computer solution of a wide variety of problems.
CSC 144 or permission of instructor.
This course enables the student educator to design and evaluate digital tools for various learning environments based on proven cognitive science illuminating how the brain processes and integrates new learning. Students will become familiar with pedagogical practices grounded in frameworks such as TPACK (Technological Pedagogical Content Knowledge) and SAMR (Substitution, Augmentation, Modification, and Redefinition) and aligned with the International Society for Technology in Education (ISTE) educator standards, the Ohio Standards for the Teaching Profession (OSTP), and the Specialized Professional Associations (SPA) standards for their area of licensure. Future educators will design technology-enhanced instruction appropriate to a variety of learners’ needs and connect their practice to a Catholic understanding of the important role of teachers in society. Finally, students seeking admission to the education program will begin the development of a personal e-Portfolio to which they will add digital artifacts as they progress through the program demonstrating their proficiency in content knowledge; classroom environments; planning, instruction and assessment; professional responsibility, technology, and diversity (meeting the distinct learning needs of P-12 students). This course is for those seeking teacher licensure.
Notes
Laptop required.
Serves three main purposes: to develop in the students an understanding of the object-oriented approaches to the algorithmic formulation of methods for problem solving on the computer; to train students to use at least one object-oriented computer language and to prepare students for applied object-oriented programming in their upper level courses.
Studies the use of scripting languages and software tools for work in bioinformatics. Emphasis will be on data manipulation, file input and output, FASTA files, regular expressions and pattern matching, databases, and web programming.
Studies the fundamental algorithms used in bioinformatics. Attention will be paid to specific algorithms (e.g. for measuring DNA similarity and for constructing phylogenic trees), to algorithm design methods (e.g. exact vs. heuristic methods, and dynamic programing) as well as to the computational costs of the various algorithms (Big-O notation, and the difference between polynomial and exponential time algorithms).
This course serves as an introduction to statistical analysis and programming with applications in the natural sciences. Topics include data entry, basic programming, statistical tests such as the t-test, ANOVA, the analysis of survey data, data visualization. Emphasis will be placed on how to select the right tool, use it competently, and interpret the results.
Introduces students to the use of computers in the nursing profession. Topics include computer fluency in office technology, electronic medical record systems, healthcare and nursing informatics, healthcare documentation, and new technologies.
Notes
Additional course fee.
Nursing Major
Further prepares student educators for the effective use of computers and technology in the classroom. Through this course, students will learn the basic skills needed to evaluate, design, produce, and utilize multimedia products in educational, organizational, and communications environments.
Introduces students to the fundamentals of network and data communication technologies. Course topics include telecommunication media and equipment; data transmission and protocols; corporate, local, and wide area networks; intranets and internets; and network software and management. An introduction to electromagnetic concepts and principles is included to provide a technical foundation for these concepts.
Studies the design and the implementation of a database. The focus is on SQL and relational databases, but some of the more recent NoSQL approaches will also be discussed.
Studies the system development cycle with emphasis on techniques and tools, system documentation, data flow diagrams, system testing, and implementation. Students are expected to suggest, design, and implement a specific application system.
Introduces procedural programming techniques using the programming language FORTRAN. Emphasis is placed on the analysis and design of numerical algorithms, which are useful in business and science. Other topics include file processing and parallel processing.
Examines the basic concepts of programming languages: programming language processors, elementary and structured data types, subprograms, sequence control, data control, storage management, syntax and translation, and programming environments. The student will also study three different programming languages and write a short project in each.
Data science is an interdisciplinary field which blends mathematics, computer science, and various domain-specific fields (such as bioinformatics). The goal is to extract usable information from large sets of data. This course will be an introduction to data science using R, Python or a similar language. Emphasis will be on exploratory data analysis, visualization, model fitting, classification, and prediction.
Computer
Science
Elective
Studies the use of simulated evolution in computer science and biology. Primary emphasis will be on the use of evolutionary and genetic algorithms as tools for solving combinatorial optimization problems (including problems arising in bioinformatics). Secondary emphasis will be placed on construction of computer models designed to illuminate aspects of evolutionary theory (e.g. the computer evolution of strategies for playing the prisoner's dilemma as a model for the evolution of altruistic traits).
Covers the fundamental algorithms used in both symmetric key and public key cryptography. Algorithms include AES, Diffie-Hellman, RSA, elliptic curve cryptography, as well as cryptographical hash algorithms. Both mathematical foundations and computer implementations will be discussed during the course.
Is designed to teach computer science and computer information science majors the skills necessary to learn computer science on their own and communicate their knowledge to others in oral and written form. All students will attend presentations made by senior computer science students. Students will be required to write a short, independently-researched paper and present it to the other students in the junior seminar.
Will introduce concepts of algorithm analysis, strategies, time and resource complexity and basic computability.
Is a seminar in information resource management covering such topics as office automation, networks, distributed data processing, data integrity, and decision support systems.
Junior standing or permission of instructor
Provide an understanding of fundamental software architecture concepts, standards, drivers, styles, and design specification tenets including design patterns. Develop an understanding of UML method notations and tools to document architectures, and use of tradeoff methodologies (e.g., QAW, ATAM) to evaluate an architecture. Present tenets of technical and ethical debt. Throughout the course students will implement a core set of software design patterns using language of choice.
Is a work-experience opportunity with the purpose of expanding education by applying accumulated knowledge in computer science/technology. The availability of internships is limited to upper-level students, normally seniors with a 2.5 quality point average. Students are approved individually by the academic department. A contract can be obtained from the Career Services Office in Starvaggi Hall. Internships count as general electives.
Computer science junior or senior standing and permission of the department chair. Internships must be preapproved.
Surveys the relationship between hardware architecture and both systems and applications software. The influence of processor and storage system architecture on software design is also studied.
Junior standing or permission of instructor
Considers the structure of operating systems involving design, implementation, and maintenance. Various types of mainframe, mini, and micro operating systems will be discussed. Some systems programming will be considered.
Is an introduction to the architecture of the microprocessors and Assembly Language. Concepts in digital logic, machine level of data, the assembly level machine organization, memory system organization, interfacing and functional organization are covered. Exercises in Assembly Programming will illustrate some of these concepts.
Gives students an opportunity to plan and implement a significant project using previously obtained analytic and programming skills. Students will be responsible for the proposal, management, implementation, documentation, and communication of the project. Departmental guidance will be available when necessary.
Explores Artificial Intelligence (AI) within the context of special languages used in AI, such as LISP and PROLOG. Basic AI techniques presented include those needed to understand and design simple expert systems. As time permits, topics from the following areas may be investigated: natural language processing, planning, machine learning, neural networks, and various forms of reasoning.
Examines the underlying mathematical models and theories that are the basis of the modern computer. Topics include grammars, types of languages, types of automata, computability, and complexity.
Requires all computer science and computer information science students to write a thesis on an approved topic in computer science. Students must consult closely with a departmental faculty member at each stage in the development of their theses. The thesis will be presented to students in the Junior Seminar.