91180

CMSC 116 Intro to Computing: Semantic Web

Robert McGrail Lab A: Lab B:

. T . . . . . . Th . . . . . F

10:10 - 11:30 am 10:30 - 12:30 pm 10:30 - 12:30 pm

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:  passing score on Part I of the Mathematics Diagnostic. This course has lab options. Class size: 20

91898

CMSC 115 Intro to Computing: Simulating Reality

Sven Anderson

.  T .Th .

3:10 -5:10 pm

RKC 100

MATC

Cross-listed: Cognitive Science How do rumors and fashions spread in society?  What properties make a  person or web page powerful?  This introduction to modeling and simulation is intended for students who are interested in answering such questions using computer modeling.  This semester we will focus on social networks and incorporate elements of game theory to explain aggregate behavior in crowds, social networks, and other structured institutions.  Students will create and explore several different simulation model types drawn from a variety of disciplines, including artificial intelligence, economics, environmental science, and political science.  Students will gain a practical understanding of how to combine mathematical modeling, computer simulation, and data analysis as they build simulation models designed to answer a practical need and/or scientific question.  No prior knowledge of computer programming is required.  Prerequisite: a passing score on Part Two of the Mathematics Diagnostic.

91183

CMSC 131 Cognitive Science

Rebecca Thomas Lab:

M . W . . . . . . F

8:30 -9:50 am 8:30 - 10:25 am

RKC 101 RKC 107

SSCI

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. Class size: 20

91550

CMSC 143 Object-Oriented Programming with Robots

Keith O'Hara Lab:

M . W . . . . . . F

10:10 - 11:30 am 10:30 - 12:30 pm

RKC 107

MATC

Cross-listed: Cognitive Science This course introduces students with prior programming experience to object-oriented design and programming through the design and implementation of mobile robot programs. The programs will enable the robot to move around the world, reacting to sensors such as obstacle detectors and a color camera.  Students will learn how to move from an informal problem statement, through increasingly precise problem specifications, to design and implementation of a solution.  Good programming habits will be emphasized. Purchase of a small personal robot (to be specified by the instructor) is recommended. Prerequisite: any Introduction to Computing course, or permission of the instructor. Class size: 20

91178

CMSC 201 Data Structures

Sven Anderson Lab:

M . W . . . . . . F

8:30 -9:50 am 8:00 -9:50 am

RKC 100

MATC

This course introduces students to essential principles of program design and analysis that underlie applications of computation to internet communication, digital media, and artificial intelligence.  Building on basic programming skills, we will focus on the construction of more sophisticated and reliable computer programs that employ the most important data structures.  Data structures, common ways in which data is organized and manipulated, are an important aspect of modern programs.  Consequently, throughout the course students will learn to create and use the most useful data structures, including files, lists, stacks, trees, and graphs. Students will write several programs, ranging from short lab assignments to larger systems of their own design. Prerequisite: CMSC 141 or 143. Class size: 20

91184

CMSC 225 Computer Architecture

Rebecca Thomas

M . W . .

3:10 -4:30 pm

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. Class size: 20

91181

CMSC 305 Design of Programming Languages

Robert McGrail

. T . Th . . W . ..

1:30 -2:50 pm 10:30 - 12:30 pm

RKC 100

MATC

Cross-listed: Cognitive Science This course will cover a selection of issues important to the design of programming languages including, but not limited to, type systems, procedure activation, parameter passing, data encapsulation, dynamic memory allocation, and concurrency. In addition, the functional, logic, and object-oriented programming paradigms will be presented as well as a brief history of high-level programming languages. Students will be expected to complete a major programming project in Standard ML of New Jersey as well as other programming assignments in Java or Prolog. Prerequisite: CMSC 201. Class size: 20

91185

CMSC 317 The Computational Image

Keith O'Hara

M . . . . . . W . .

1:30 -2:50 pm 12:50 -2:50 pm

RKC 100

MATC

This course covers computational techniques for the analysis and synthesis of digital images.  Using algorithms and approaches from computational geometry, computer graphics, image processing, computer vision, and augmented reality, students will build computer systems that are visually interactive. This course covers topics such as image formation, feature extraction, object segmentation, recognition, and tracking, rendering, and multi-view geometry. Prerequisite: Computer Science 201 or permission of the instructor. This course coincides with Sculpture II: Video Installation, jointly meeting several times over the semester for workshops and exhibitions. Class size: 20