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Schedule of Classes

 

Summer Session I 2017

 

Computer Science
Yun Wang • Bradley Hall 185 • 309-677-3284
CS498Directed Individual Studies in Computer Science (1 to 3 hours)
Prerequisite: Consent of instructor.
 04 *R* Arr     Alexander Uskov  
CS562Intelligent Systems and Applications (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 course in statistics.
 01 Arr     C Nikolopoulos  
CS572Advanced Topics in Databases (3 hours)
Prerequisite: Graduate standing in CS or CIS, or senior standing in CS or CIS, or CS 370 or equivalent.
 01 Arr     C Nikolopoulos  
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 Arr     Vladimir Uskov Online Course
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 Arr     Young Park  
CS625Operating Systems Design (3 hours)
Prerequisite: Graduate standing in CS or CIS, or CS 321 or equivalent.
 01 Arr     Jiang B Liu Online Course
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
 "Programming in Python"
CS698Directed Individual Studies in Computer Science (1 to 3 hours)
Prerequisite: Consent of instructor.
Registration in section 01 is for 3 credit hours.
 01 *R* Arr     C Nikolopoulos  
 02 *R* Arr     Alexander Uskov Online Course
 03 *R* Arr     Young Park  
 04 Canceled
 05 *R* Arr     Vladimir Uskov  
 
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.
Gives the necessary background and practice for building intelligent systems using three of the most commercially successful applications of AI: the logical approach (expert systems, fuzzy logic, and fuzzy expert systems), the biological approach (neural networks, evolutionary programming, and genetic algorithms), and the statistical approach (Bayesian networks, belief networks, Markov chain, Hidden Markov models, and statistical and neural-based clustering). Students will have the opportunity to build integrated, hybrid intelligent systems to solve problems in a variety of applications including in the medical domain, financial domain and stock market, and autonomous robotics systems.
Designing and building enterprise-wide data warehouses. Techniques for analyzing data in data warehouses. Study different types of data models including logic and object-oriented databases. Advanced topics in relational databases such as multimedia databases, distributed databases, concurrency, security, etc.
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).
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.
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