98106

CMSC 116 Introduction to Computing: Semantic Web

Robert McGrail

M . . . . Lab A: T

1:30 -2:50 pm 3:00 -5:00 pm

RKC 103 RKC 100

MATC

Cross-listed: Cognitive Science This course is an introduction to semantically intelligent content management for the World Wide Web. Participants in this course will construct social networking software, similar in scope to weblogs or facebook, using an advanced content management system. Strong emphasis will be placed on the development of flexible applications that efficiently store and process data and metadata. In addition to basic computer programming, various XML technologies will be introduced and employed. Prerequisite: eligibility for Q coursesThis course has lab options. See below.

98106

CMSC 116 Introduction to Computing: Semantic Web

Robert McGrail

M . . . . Lab B: W

1:30 -2:50 pm 1:00 -3:00 pm

RKC 103 RKC 100

MATC

This course has lab options. See above.

98509

CMSC 131 Cognitive Science

Sven Anderson

. T . Th . Lab: . . F

1:00 -2:20 pm 1:30-3:30 pm

RKC 103 RKC 107

SLSCI

Cross-listed: Cognitive Science, Philosophy, Psychology How do brains make minds? Can computers think? Is my dog conscious? Cognitive science assumes that the brain is some sort of computational engine, and, beginning with that premise, attempts to find answers to such questions. This course will be taught by faculty from biology, computer science, linguistics, philosophy, and psychology, who will combine their different approaches to explore how humans and other intelligent systems feel, perceive, reason, plan, and act. In particular, the course will focus on the fundamental importance of language, signaling, and representation at many levels, from the neural to the organismal. Laboratories will provide students with hands-on experience analyzing neural and behavioral data as well as with computational modeling. Prerequisites: pre-calculus or its equivalent and a willingness to engage a broad variety of ideas and approaches from the natural, mathematical, and social sciences.

98104	CMSC 141 Computer Science I	Sven Anderson	M . W . .	3:00 -4:30 pm	RKC 100	MATC
			Lab: F	3:30 -5:30 pm	RKC 100

Cross-listed: Cognitive Science Creating computer software typically begins with an informal problem statement and perhaps a vague idea for a solution, and proceeds through progressive refinement of both our understanding of what the problem is and our understanding of how to solve it. In object-oriented programming, these two kinds of refinement often mesh as we design and build software objects that model important aspects of the problem and of its solution. This course, which is intended for students with prior programming experience, introduces students to the methodology of object-oriented design and development via guided student work, solving interesting problems drawn from such arenas as graphics and animation, simulation, and/or Internet applications. Good programming and documentation habits are emphasized. Prerequisite: any Introduction to Computing course or permission of the instructor.

98105	CMSC 201 Data Structures	Greg Landweber	M . W . .	9:00 - 10:20 am	RKC 107	MATC
			Lab: F	9:00 - 11:00 am	RKC 100

Cross-listed: Cognitive Science This course covers the implementation and use of advanced data structures such as stacks, queues, hash tables, binary search trees, sets, and graphs via an object-oriented programming language. Prerequisite: CMSC 141.

98108

CMSC 225 Computer Architecture

Rebecca Thomas

M . W . F

10:30 - 11:50 am

RKC 107

MATC

This course is an introduction to the structure and operation of a modern computer architecture. Topics will include instruction sets, pipelining, instruction-level parallelism, caches, memory hierarchies, storage systems and multiprocessors. Assembly language programming will be used to demonstrate the concepts. Prerequisites: Computer Science 141, with Physics 212 recommended.

98107

CMSC 335 Computer Networks

Robert McGrail

M . W . .

9:00 - 11:00 am

RKC 100

MATC

This course takes a bottom-up approach to computer networking, covering in detail the physical, data link, MAC, network, transport, and application layers. TCP/IP and OSI reference models are introduced with examples taken from the Internet, ATM networks, and wireless networks.

Prerequisite: Computer Science 142.

98109

CMSC 351 Artificial Intelligence

Rebecca Thomas

. T . Th .

9:00 - 10:20 am

RKC 100

MATC

This course provides a broad introduction to topics in artificial intelligence, including knowledge representation and reasoning, planning and problem solving, and machine learning. Advanced topics may include natural language processing, multi-agent systems, image processing, or other topics of the instructor's choice. Prerequisite: Computer Science 142.