Computer Science/CS - Undergraduate Course Descriptions

Note: See quarterly class schedule or departmental advisor for further enrollment restrictions, requirements, or special course information.

141-4 Computer Programming I

Introduction to use of computers as a problem-solving tool. Examples from and applications to a broad range of problems. Methodology for algorithm design and for structured modular implementation is stressed. Three hours lecture, two hours lab. Prerequisite: MTH 127 or at least level four on math placement test.

142-4 Computer Programming II

Concepts introduced in CS 141 are developed in greater detail and depth. Emphasis on verification and testing of programs. Three hours lecture, two hours lab. Prerequisite: CS 141.

205-4 Introduction to Computers & Office Productivity Software

Focus on learning MS Office software applications including word processing (intermediate), spreadsheets, database and presentation graphics using a case study approach where critical thinking and problem solving skills are required. Two hours lecture, four hours lab.

206-4 Computer Software Productivity Tools

Advanced use of application software to increase productivity. Covers sharing data and files among different packages, spreadsheet macros, and database integration. Prerequisite: CS 205 or waiver.

207-4 Advanced Office Productivity

Emphasis is placed on understanding how packages interact within an integrated environment. Personal computers are used for sophisticated word processing and desktop publishing projects. State-of-the-art presentation techniques such as hypertext will be discussed. Prerequisite: CS 206

208-4 Computer Programming for Business I

Introduces basic concepts of programming. Examples are from business applications and display graphics. Emphasis is on problem solving with the computer as a tool. Prerequisite: CS 205, MTH 129.

209-4 Computer Programming for Business II

Continuation of CS 208. Introduces the basic concepts of programming. Examples are from business applications and display graphics. Emphasis is on problem solving with the computer as a tool. Prerequisite: CS 208.

214-4 Visual Basic Programming

An introductory course to the use of graphic objects in a windows event-driven environment providing a case study of object-oriented programming with Visual Basic in Microsoft Windows to develop simple graphic user interfaces. Need to be familiar with programming concepts.

240-4 Computer Programming I

Basic concepts of programming and programming languages are introduced. Emphasis is on problem solving and object oriented programming. Prerequisite: MTH 130 or MPL 5.

241-4 Computer Programming II

A continuation of CS 240. Emphasis is on solving more complex problems using object oriented programming. Prerequisite: CS 240.

242-4 Computer Programming III

Advanced concepts of computer programming are explored. Emphasis is on use of data structures and tools that facilitate programming. Prerequisite:(CS 241, MTH 257) or CEG 221.

271-4 Intro to Bioinformatics

(Also listed as BIO 271) Tools-oriented approach to bioinformatics emphasizing data structure in DNA, string representation in PERL, data searches, pairwise alignments, substitution patterns, protein structure prediction and modeling, proteomics, and the use of web-based bioinformatic tools. Prerequisite: BIO 112, CS 240.

302-4 Introduction to Oracle/SQL Databases

Relational client server database design and accesstechniques. Includes building database tables, writing SQL statements/programs, and developing user interfaces and reports for data retrieval using Internet. Prerequisite: CS 240 or CS 141 or CS 208.

316-4, 317-4 Numerical Methods for Digital Computers I and II

Introduction to numerical methods used in the sciences. Methods of interpolation, data smoothing, functional approximation, integration, solutions of systems of equations, and solutions of ordinary differential equations. Three hours lecture, two hours lab. Prerequisite: FOR 316: (CS 142 or EGR 153 or CS 241 or CEG 220) and MTH 231 and (MTH 253 or 235 or 255) FOR 317: CS 316 and (MTH 233 or 235) and (MTH 235 or 253 or 355).

340-1 Programming Language Workshop

Self-directed study in computer languages. Individual workshops are offered in significant languages such as JAVA, COBOL, PL/1, SNOBOL, LISP, SIMSCRIPT, C#, and GPSS. May be taken for letter grade or pass/unsatisfactory. Prerequisite: CS 400.

350-4 Computational Tools and Techniques for Data Analysis

Introduction to the representation, visualization, and modeling of large data sets. Data analysis using standard high level software tools. Topics include data filtering, clustering, classification, and data mining.Prerequisite: none

399-1 to 5 Selected Topics

Selected topics in computer science. May be taken for letter grade or pass/unsatisfactory.

400-4 Data Structures and Algorithms

Study of the implementation of data structures and control structures in professional computer programs. Introduction to the fundamentals of complexity and analysis. Study of common standard problems and solutions (e.g., transitive closure and critical path). Emphasis on high-level language software design. Three hours lecture, two hours lab. Prerequisite: CS 242 and CEG 233.

405-4 Introduction to Database Management

Survey of logical and physical aspects of data basemanagement systems, including entity-relationship and relational data models; physical implementation methods; query languages; SQL, relational algebra, relational calculus, and QBE; experience in creating and manipulating databases. Prerequisite: CS 400.

407-3 Optimization Techniques

(Also listed as MTH 407.) Concepts of minima and maxima; linear programming; simplex method, sensitivity, and duality; transportation and assignment problems; and dynamic programming. Prerequisite: MTH 233 and 253 or 255.

409-4 Principles of Artificial Intelligence

Problem-solving methods in artificial intelligence (AI) with emphasis on heuristic approaches. Topics include methods of representation, search, intelligent agents, planning, learning, natural language processing, logic, inference, robotics, and case-based reasoning. Three hours lecture, two hours lab. Prerequisite: CS 400 and CS 340 (LISP) or LISP programming experience.

410-4 Theoretical Foundations of Computing

(Also listed as MTH 410.) Turing machines; partial-recursive functions; equivalence of computing paradigms; Church-Turing thesis; undecidability; intractability. Three hours lecture, two hours lab. Prerequisite: CS 466.

415-3 Social Implications of Computing

Examines the impact of computers and computing on society. Topics include privacy, dangers introduced by computers performing critical tasks, the effect of robots on the work force, the impact of computers on education, and the new legal issues introduced by computing. Senior standing.

419-3 Cryptography and Data Security

(Also listed as MTH 419.) Introduction to the mathematical principles of data security. Various developments in cryptography are discussed, including public-key encryption, digital signatures, the data encryption standard (DES), and key safeguarding schemes. Prerequisite: MTH 253 or 255.

458-3 Applied Graph Theory

(Also listed as MTH 458.) Introduction to methods, results, and algorithms from graph theory. Emphasis on graphs as mathematical models applicable to organizational and industrial situations. Prerequisite: CS 142 or 241, MTH 231.

459-3 Combinatorial Tools for Computer Science

(Also listed as MTH 459.) Introduction to some of the mathematical tools needed for an understanding of computer programming. The topics covered are summations, elementary number theory, combinatorial identities, generating functions, and asymptotics. MTH 457 recommended. Prerequisite: MTH 280.

466-4 Introduction to Formal Languages

Introduction to the theory of formal languages and automata. Emphasis is on those classes of languages commonly encountered by computer scientists (e.g., regular and context-free languages). Prerequisite: CS 400, MTH 257; or MTH 257 and completion of a 400-level math or statistics course

470-4 Systems Simulation

Introduction to simulation and comparison with other techniques. Discrete simulation models. Introduction to queuing theory and stochastic processes. Comparison of simulation languages. Simulation methodology and selected applications. Three hours lecture, two hours lab. Prerequisite: CS 400 and (STT 360 orSTT 363 or ISE 301).

471-4 Algorithms for Bioinformatics

Theory-oriented approach to the application of contemporary algorithms to bioinformatics. Graph theory, complexity theory, dynamic programming and optimization techniques are introduced in the context of application toward solving specific computational problems in molecular genetics. Prerequisite: BIO 271, CS 400, BIO 210 and BIO 211, CHM 213

480-4 Comparative Languages

Basic concepts and special-purpose facilities in programming languages examined through several representative languages. Three hours lecture, two hours lab. Prerequisite: CS 400.

482-4 Scanning, Parsing, and Semantic Analysis

Study and use of tools for performing lexical, syntactic, and semantic analysis of computer-oriented languages. Prerequisite: CS 466 and CS 480.

495-4 Undergraduate Thesis

Completion of a computer science research project. Writing and defending a thesis that describes the research and summarizes the results. Prerequisite: CS 499. Graded pass/unsatisfactory.

499-1 to 5 Selected Topics

Selected topics in computer science. May be taken for letter grade or pass/unsatisfactory, at instructor's option.