92512

CMSC 115

INTRO TO COMPUTING:

Simulating Reality

Sven Anderson

M W 10:10 am – 11:30 am

RKC 100

MATC

Cross-listed: Mind, Brain & Behavior How do rumors, fashions and viruses spread? What properties make a person or web page important? This introduction to modeling and simulation is intended for students who are interested in answering such questions using computer modeling. The models we build will emphasize situations such as animal herds and social networks in which a large number of individuals interact, thereby creating interesting aggregate phenomena such as flocking and small-world networks. Students will create and explore several different simulation model types drawn from a variety of disciplines, including artificial intelligence, economics, ecology, and political science. They 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: strong background in pre-calculus mathematics or its equivalent and a passing score on Part Two of the Mathematics Diagnostic. Class size: 20

92247

CMSC 141

Object-Oriented ProgRAMMING

Kerri-Ann Norton

Keith O’Hara

M W 10:10 am-11:30 am

RKC 103

MATC

This course introduces students to the methodologies of object-oriented design and programming, which are used throughout the Computer Science curriculum. Students will learn how to move from informal problem statement, through increasingly precise problem specifications, to design and implementation of a solution for problems drawn from areas such as graphics, animation, simulation. Good programming and documentation habits are emphasized. Class size: 36

LAB OPTIONS (register separately)

92248

CMSC 141 LBA

Object-Oriented Prog LAB A

Kerri-Ann Norton

F 10:30 am-12:30 pm

RKC 107

MATC

Class size: 18

92249

CMSC 141 LBB

Object-Oriented Prog LAB B

Keith O’Hara

F 1:30 pm-3:30 pm

RKC 107

MATC

Class size: 18

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91761

CMSC 201

data structures

Keith O’Hara

M W 8:30 am – 9:50 am

F 8:30 am – 10:30 am

RKC 107

MATC

Cross-listed: Mind, Brain, Behavior 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, or permission of the instructor. Class size: 18

92263

CMSC 210

PROGRAMMING NATURE: MODELING BIOLOGICAL AND PHYSICAL SYSTEMS

Kerri-Ann Norton

T Th 3:10 pm – 4:30 pm

RKC 100

MATC

This course introduces students with prior programming experience to the applications of object-oriented programming to physical and biological systems. The students will develop the necessary tools for modeling biological and physical objects that can move, interact, divide, and evolve, with a specific application of simulating biological cells. The students will learn how to pose a question about a natural system, develop a set of rules, and implement simulations to formulate predictions about the dynamics of that system. Prerequisite: CMSC 143 or permission by the instructor. Class size: 18

91762

CMSC 251

Intro to Artificial Intelligence

Sven Anderson

M W 1:30 pm-2:50 pm

RKC 107

MATC

Cross-listed: Mind, Brain, Behavior An introduction to artificial intelligence principles and techniques with an emphasis on elements of artificial intelligence that are compatible with biologically-based intelligence (e.g., neural computation). This course is intended to provide a first course in artificial intelligence, particularly for students interested in cognitive science and neuroscience. The course will explore the application of artificial intelligence techniques to particular application areas. Techniques include automated reasoning, machine learning, evolutionary learning, heuristic search, and behavior-based robot control. Application examples will be drawn from artificial life, robotics, game play, logic, visual perception, and natural language processing. Prerequisites: CMSC 143, 157, or equivalent programming experience.

Class size: 18

91763

CMSC 305

Design of Programming Languages

Robert McGrail

Lab:

T Th 1:30 pm-2:50 pm

F 1:30 pm-3:30 pm

RKC 100

MATC

Cross-listed: Mind, Brain, Behavior 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 Data Structures. Class size: 18

91764

CMSC 321

Databases: Theory & Practice

Robert McGrail

Lab:

T Th 8:30 am-9:50 am

F 8:30 am-10:30 am

RKC 100

MATC

An introduction to the design, implementation, and uses of databases. Topics include database design, database models, integrity, concurrency, security, and database query languages. Prerequisite: a 100-level Computer Science course. Class size: 18