CS 498

Spring 2014 All Classes

All Classes

Special Topics

Credit: 0 TO 4 hours.

Subject offerings of new and developing areas of knowledge in computer science intended to augment the existing curriculum. See Class Schedule or departmental course information for topics and prerequisites.

May be repeated in the same or separate terms if topics vary.

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CS 498 class schedule data for spring 2014
CRN	Type	Section	Time	Day	Location	Instructor	Section Details
60162	Lecture-Discussion Lecture-Discussion	374 374	12:30PM -1:45PM 1:00PM -1:50PM	TR WF	1109 Siebel Center for Comp Sci 1109 Siebel Center for Comp Sci	Pitt, L Erickson, J Pitt, L Erickson, J	Part of Term: 1 Date Range: 01/21/14-05/07/14 Credit: 4 hours Section Title: Algorithms and Models of Comp Section Info: This course will not count towards CS 400 level elective credit -- but will replace the requirements to take CS 373 and CS 473 Restriction(s): Restricted to Computer Engineering or Computer Science or Statistics & Computer Science or Math & Computer Science or Computer Sci & Anthropology or Computer Sci & Astronomy or Computer Sci & Chemistry or Computer Sci & Linguistics major(s).
31601	Lecture	CC3	2:00PM -3:15PM	TR	1310 Digital Computer Laboratory	Campbell, R Farivar, R	Part of Term: 1 Date Range: 01/21/14-05/07/14 Credit: 3 hours Section Title: Cloud Computing Section Info: CS498 Cloud Computing Topic: This course serves as an introduction to Cloud Computing. The class includes Infrastructure as a Service, Software as a Service, and Platform as a service, Map Reduce and Big Data, as well as privacy and legal issues. The class will include the problems and solutions to cloud computing, including hands on laboratory experiments (Hadoop, Hive, Storm, Hbase, ?). Topics include scheduling, resource allocation, energy efficiency, security and monitoring, availability and consistency, data center networks, pricing model, applications and extensions of the cloud platform. Case studies will be drawn from Yahoo, Google, Twitter, Facebook, scientific computation, data mining and machine learning.
59276	Lecture	CC4	2:00PM -3:15PM	TR	1310 Digital Computer Laboratory	Campbell, R Farivar, R	Part of Term: 1 Date Range: 01/21/14-05/07/14 Credit: 4 hours Section Title: Cloud Computing Section Info: CS498 Cloud Computing Topic: This course serves as an introduction to Cloud Computing. The class includes Infrastructure as a Service, Software as a Service, and Platform as a service, Map Reduce and Big Data, as well as privacy and legal issues. The class will include the problems and solutions to cloud computing, including hands on laboratory experiments (Hadoop, Hive, Storm, Hbase, ?). Topics include scheduling, resource allocation, energy efficiency, security and monitoring, availability and consistency, data center networks, pricing model, applications and extensions of the cloud platform. Case studies will be drawn from Yahoo, Google, Twitter, Facebook, scientific computation, data mining and machine learning. Restriction(s): Restricted to Graduate - Urbana-Champaign.
43751	Lecture-Discussion	MP3	2:00PM -3:15PM	WF	1105 Siebel Center for Comp Sci	Parthasarathy, M	Part of Term: 1 Date Range: 01/21/14-05/07/14 Credit: 3 hours Section Title: Logic Section Info: Topic: Logic
61019	Lecture-Discussion	OSP	ARRANGED	n.a.	ARR Siebel Center for Comp Sci	Woodley, M	Part of Term: 1 Date Range: 01/21/14-05/07/14 Special Approval: Instructor Approval Required Credit: 3 hours Section Title: Open Source Project
59208	Lecture-Discussion	U	3:30PM -4:50PM	TR	1105 Siebel Center for Comp Sci	Clifton, R	Part of Term: 1 Date Range: 01/21/14-05/07/14 Credit: 3 hours Section Title: Using Tech to Solve Adv Probs Section Info: Meets with ADV 490. This project-based course will allow teams of media and computer science students to use technology platforms to solve problems supplied by industry clients. Each student will bring their expertise to the problem at hand. Media students will learn capabilities and limitations of different technology platforms will learn how the end user will be impacted by technology decisions, and how they can help achieve advertising objectives with their code design. Junior or Senior standing. Computer Science students should have a knowledge of coding in various platforms. Restriction(s): Restricted to Computer Engineering or Computer Science major(s).