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Schedule of Classes

 

Fall Semester 2018

 

Computer Science
Steven Dolins • Bradley Hall 185 • 677-3284
CS100Introduction to Programming Concepts and LanguagesGenEd: FS   Core: QR(3 hours)
Prerequisite: MTH 109 or higher
Course Surcharge: $20 per credit hour
 01 TT6:00 PM -7:15 PM BR290 Tim Applegren  
CS101Introduction to ProgrammingGenEd: FS   Core: QR(4 hours)
Prerequisite: MTH 109 or higher
Course Surcharge: $20 per credit hour
 01 TT10:30 AM -12:15 PM BR160 Adam Byerly  
 02 MW1:00 PM -2:45 PM BR160 Adam Byerly  
 03 MW6:30 PM -8:15 PM BR180 Craig Cooper  
 04 MW10:00 AM -11:45 AM BR180 Yun Wang  
 05 MW4:30 PM -6:15 PM BR180 Craig Cooper  
CS102Data Structures (3 hours)
Prerequisite: A grade of C or better in CS 101.
Course Surcharge: $20 per credit hour
 01 TT9:00 AM -10:15 AM BR180 Yun Wang  
 02 Canceled
CS140Advanced Programming Concepts and Languages (3 hours)
Prerequisite: CS 102
Course Surcharge: $20 per credit hour
 01 MW10:00 AM -11:15 AM BR290 Jonathan Scott Williams  
 02 MW5:00 PM -6:15 PM BR290 Jonathan Scott Williams  
 03 MW1:00 PM -2:15 PM BR290 Jonathan Scott Williams  
CS210Advanced Data Structures and Algorithms (3 hours)
Prerequisite: grade of C or better in both CS 102 and CS 140 or equivalents; MTH 120 or equivalent.
Course Surcharge: $20 per credit hour
 01 MW10:30 AM -11:45 AM BR150 Young Park  
CS215Computability, Formal Languages, and Heuristics (3 hours)
Prerequisite: CS 210 or CIS 210 or equivalents; MTH 122 or equivalent.
 01 TT9:00 AM -10:15 AM BR156 C Nikolopoulos  
 02 MW9:00 AM -10:15 AM BR156 C Nikolopoulos  
CS220Computer Architecture (3 hours)
Prerequisite: CS 140 or equivalent.
 01 MW3:00 PM -4:15 PM BR180 Jiang B Liu  
CS321Operating Systems (3 hours)
Prerequisite: CS 220.
 01 TT12:00 PM -1:15 PM BR180 Jonathon Doran  
 02 MW1:00 PM -2:15 PM BR180 Jonathon Doran  
CS360Fundamentals of Data Science (3 hours)
Prerequisite: CS 101 and CS 102 or equivalent.
 01 TT12:00 PM -1:15 PM BR150 David Brennan  
CS480Social and Professional Issues in Computing (2 hours)
Prerequisite: CS 210 or CIS 210 or equivalent; or consent of instructor.
 01 Tu6:00 PM -7:50 PM BR142 Jonathan Scott Williams  
CS481Professional Practicum in Computer Science (0 to 3 hours)
Prerequisite: CS or CIS junior or senior student in good standing; consent of department chair.
 01 *R* Arr     Steven Dolins  
CS490Capstone Project I (3 hours)
Prerequisite: CS 370, CS 390 or equivalents.
 01 MW9:00 AM -10:15 AM BR150 Steven Dolins Hybrid Course
 02 *R* MW9:00 AM -10:15 AM BR150 Young Park  
 03 *R* MW9:00 AM -10:15 AM BR150 David Brennan  
 04 *R* Arr     Jonathan Scott Williams  
CS497Topics in Computer Science (3 hours)
Prerequisite: Consent of instructor.
 01 TT9:00 AM -10:15 AM BR150 David Brennan  
CS498Directed Individual Studies in Computer Science (1 to 3 hours)
Prerequisite: Consent of instructor.
 01 *R* Arr     C Nikolopoulos  
 03 *R* Arr     Steven Dolins  
 04 *R* Arr     Jonathon Doran  
 05 *R* Arr     Tachun Lin  
 06 *R* Arr     Christopher Alvin  
CS502Advanced Programming (3 hours)
Prerequisite: Graduate standing. Consent of graduate program coordinator; at least two semesters of programming experience.
 01 MW1:00 PM -2:15 PM BR150 Jiang B Liu  
CS514Algorithms (3 hours)
Prerequisite: Graduate standing in CS or CIS, or senior standing in CS or CIS, or CS 210 or CIS 210 or equivalent and one semester of statistics.
 01 TT12:00 PM -1:15 PM BR100 Young Park  
CS520Advanced Computer Architecture (3 hours)
Prerequisite: Graduate standing in CS or CIS, or senior standing in CS or CIS, or CS 220 or equivalent.
 01 TT1:30 PM -2:45 PM BR180 Jiang B Liu  
CS531Web Development Technologies (3 hours)
Prerequisite: Graduate standing in CS or CIS, or senior standing in CS or CIS, or CS 102 or equivalent.
 01 Canceled
CS563Knowledge Discovery and Data Mining (3 hours)
Prerequisite: Graduate standing in CS or CIS. Consent of instructor for all other students with graduate standing.
 01 TT10:30 AM -11:45 AM BR156 C Nikolopoulos  
CS571Database Management Systems (3 hours)
Prerequisite: Graduate standing in CS or CIS, or senior standing in CS or CIS, or CS 210 or CIS 210 or equivalent.
 01 MW9:00 AM -10:15 AM BR160 Adam Byerly  
CS572Distributed Databases and Big Data (3 hours)
Prerequisite: Graduate standing in CS or CIS, and CS 571. Consent of instructor for all other students with graduate standing.
 01 TT6:00 PM -7:15 PM BR270 Steven Dolins  
CS590Fundamentals of Software Engineering (3 hours)
Prerequisite: Graduate standing in CS or CIS, or senior standing in CS or CIS, or CS 390 or equivalent.
 01 Canceled
 02 M4:30 PM -7:15 PM BR160 Vladimir Uskov  
CS591Software Project Management (3 hours)
Prerequisite: Graduate standing in CS or CIS, or senior standing in CS or CIS, or CS 390 or equivalent, or consent of instructor.
 01 W4:30 PM -7:15 PM BR160 Vladimir Uskov  
CS592Requirements Development (3 hours)
Prerequisite: Graduate standing in CS or CIS, or senior standing in CS or CIS, or CS 210 or CIS 210 or equivalent, or consent of instructor.
 01 Canceled
CS612Automata, Computation and Complexity (3 hours)
Prerequisite: Graduate standing in CS or CIS, or CS 502 or equivalent.
 01 Canceled
CS625Operating Systems Design (3 hours)
Prerequisite: Graduate standing in CS or CIS, or CS 321 or equivalent.
 01 Canceled
CS681Professional Practicum in Computer Science (0 hours)
Prerequisite: Graduate CS or CIS student in good standing; consent of department chair and graduate program director.
 01 *R* Arr     Steven Dolins  
CS697Advanced Topics in Computer Science (3 hours)
Prerequisite: Consent of instructor.
 01 Canceled
 02 *R* Arr     Vladimir Uskov  
CS698Directed Individual Studies in Computer Science (1 to 3 hours)
Prerequisite: Consent of instructor.
 01 *R* Arr     Steven Dolins  
 02 Arr     Vladimir Uskov  
 03 *R* Arr     C Nikolopoulos  
 "Data MiningInterrelat"
 06 *R* Arr     Young Park  
 "CONTEXT AWARE REC.SYS"
 07 *R* Arr     Staff  
 08 *R* Arr     Tachun Lin  
CS699Thesis in Computer Science (0 to 6 hours)
Prerequisite: Consent of department chair
 01 *R* Arr     Steven Dolins  
 
An introduction to programming concepts and languages for non-Computer Science (CS) majors. Topics include the structure and design of algorithms, variables, constants, data types, arithmetic operations, selection and repetition structures, functions, input/output, arrays, structures, files, libraries. Students will design, write, test and run computer programs using a modern programming language as the development tool.
Introduces the fundamental concepts of programming from an object-oriented perspective. Topics include simple data types, control structures (if-else loops, switch statements), introduction to array and string data structures, algorithms, debugging and testing techniques, and social implications of computing. The course emphasizes good software engineering principles and practices, breaking the programming process into analysis, design, implementation, and testing, with primary focus on implementation and development of fundamental programming skills.
Introduction to concepts of object-oriented programming with review of control structures and data types and array processing. Introduction to the object-oriented programming paradigm, focusing on the definition and use of classes along with the fundamentals of object-oriented design. Overview of programming principles, simple analysis of algorithms, searching and sorting techniques, and an introduction to software engineering issues.
Advanced programming concepts and languages appropriate to computer science and computer information systems. Topics include dynamic memory management, garbage collection, advanced object-oriented concepts, generic programming, exception handling, recursion, overloading.
Advanced topics in object-oriented programming with an emphasis on advanced data structures, algorithms, and software development.
Theory of computation and formal languages, grammars, computability, complexity, algorithms, heuristics, and foundations of intelligent systems.
Basics of logic circuit design, modern processor architecture, and assembly language. Overview of principle issues of internal system architecture, including memory, buses, and peripherals.
Fundamentals of operating systems concepts, design, and implementation. Topics include operating system components and structures, process and thread model, mutual exclusion and synchronization, scheduling algorithms, memory management, I/O controls, file systems, and security.
Introduction to the knowledge acquisition and discovery process. Cleaning and analyzing data, building machine learning models, model validation and testing, and visualization. A number of machine learning algorithms are introduced such as regression, naive Bayes, decision trees, association rules, and clustering. Feature selection and transformation. Introduction to Distributed Databases and Big Data. Programming languages, such as R and Python are covered at an accelerated pace, as the course assumes as prerequisites two semesters of programming. Emphasis is on the use of such languages for data analysis and modeling.
Introduction to the social and professional issues and practices that arise in the context of computing.
Special projects under staff supervision on professional practicum in computer science, with near-term economic benefit. Repeatable to a maximum of 3 credit hours.
Applies the concepts and skills learned by undergraduate computer science majors at Bradley University. Students are required to work on a team on a significant software project.
Topics of special interest in computer science area which may vary each time course is offered. Repeatable under a different topic for a maximum of six semester hours.
Individual study or research/development project under supervision of a CS&IS faculty member. May be repeated under a different topic once. Repeatable to a maximum of six semester hours.
Introduces the fundamental concepts of programming from an object-oriented perspective with emphasis on advanced programming skills and good software development principles in a closed laboratory setting. Covers topics including object-oriented paradigm, design and programming, fundamental data structures and computing algorithms, and software development principles. If needed, course should be taken during first regular semester at Bradley. Credit for this course does not count towards graduation requirements in any graduate program within the Department of Computer Science and Information Systems.
Design and analysis of algorithms. Dynamic structures maintenance and hashing. Searching, sorting, and traversal. Time and space requirements; simplification; computational complexity; proof theory and testing; NP-hard and NP-complete problems.
Fundamental computer sub-systems: central processing unit; memory systems; control and input/output units. General purpose computing systems design. Examples from existing typical computers.
ntroduction to PERL/CGI, XHTML, XML, JavaScript and scripting languages. Web page design and layout. Client and server side development of web applications. Database connectivity, Java Database Connectivity (JDBC).
Brings together the latest research in statistics, databases, machine learning, and artificial intelligence that are part of the rapidly growing field of knowledge discovery and data mining. Topics covered include fundamental issues, classification and clustering, machine learning algorithms, trend and deviation analysis, dependency modeling, integrated discovery systems, next generation database systems, data warehousing, and OLAP and application case studies. Cross-listed with CS 463. For cross-listed undergraduate/graduate courses, the graduate-level course will have additional academic requirements beyond those of the undergraduate course.
Relational database design, including entity relationship modeling and normalization. Structured query language (SQL) for creating and querying databases. Other topics include the theory of relational databases, including relational algebra, various loading and reporting utilities, and the implementation of database management systems, e.g., how query optimization works.
Designing and building enterprise-wide data warehouses. Cover topics related to large distributed databases, including designing distributed databases, replicating data, and concurrency. NoSQL, object-oriented, and multimedia databases and their query languages. Cross-listed with CS 472. For cross-listed undergraduate/graduate courses, the graduate-level course will have additional academic requirements beyond those of the undergraduate course.
Software engineering: software product; prescriptive process models; system engineering; analysis modeling; design engineering; architectural design; user interface design; testing strategies and techniques; software systems' implementation; software systems' maintenance.
Methods of PMBOK-based management of software systems design and development projects, including systems view, main project management process groups and knowledge areas, management plans, project metrics and estimates, tools for project management, project reports and documentation. Cross listed with CIS 491 and CIS 591 courses. For cross listed undergraduate/graduate courses, the graduate level course will have additional academic requirements beyond those of the undergraduate course.
Covers topics including basic concepts and principles of software requirements engineering, the requirements engineering process, requirements elicitation, requirements analysis, requirements specification, system modeling, requirements validation and requirements management, and techniques, methods, and tools for requirements engineering and software systems requirements modeling (including structured, object-oriented and formal approaches to requirements modeling and analysis).
Theory of formal languages and computability, Automata, Turing machines, grammars. Context free and context sensitive languages; parsing. Recursion theory; limits of effective computability, P and NP class of problems, NP-complete problems. Non Turing computable problems, reducibility, complexity.
Advanced concepts in operating system design. Topics include process and thread management, virtual memory, interprocess communication, distributed systems, parallel and distributed file system designs, resource management, and security and protection.
Special projects under Smith Career Center supervision on student's professional practicum in corporate/business environment in computer science, with near-term economic benefit. Satisfactory/Unsatisfactory. Minimum of 5-10 hours per week required.
Special projects under staff supervision on advanced problems in numerical or non-numerical branches of computer science. May be taken more than once under different topics for a maximum of 6 semester hours.
Individual study in an area of computer science relevant to the student's professional goals and not covered in a formal course offered by the department. May be repeated twice for a maximum of 6 credit hours.
Computer science research and thesis preparation. Required of candidates choosing the thesis option. Total of 6 semester hrs. to be taken in one or two semesters.
This course meets a General Education requirement.
C1 - English Composition
C2 - English Composition
SP - Speech
MA - Mathematics
WC - Western Civilization
NW - Non-Western Civilization
FA - Fine Arts
HL - Human Values - Literary
HP - Human Values - Philosophical
CD - Cultural Diversity
SF - Social Forces
FS - Fundamental Concepts in Science
TS - Science & Technology in the Contemporary World
This course meets a Core Curriculum requirement.
OC - Communication - Oral Communication
W1 - Communication - Writing 1
W2 - Communication - Writing 2
FA - Fine Arts
GS - Global Perspective - Global Systems
WC - Global Perspective - World Cultures
HU - Humanities
NS - Knowledge and Reasoning in the Natural Sciences
SB - Knowledge and Reasoning in the Social and Behavioral Sciences
MI - Multidisciplinary Integration
QR - Quantitative Reasoning
This section meets a Core Curriculum requirement.
EL - Experiential Learning
IL - Integrative Learning
WI - Writing Intensive
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