11377 |
CMSC 116 Introduction to Computing: Web Informatics |
Robert McGrail Lab A: Lab B: |
. T . . . . . . Th . . . . F. |
1:30 pm -2:50 pm 1:30 pm -3:30 pm 1:30 pm -3:30 pm |
RKC 103 RKC 100 RKC 100 |
MATC |
This course is an introduction to content deployment for the World Wide Web. Participants in this course will construct social networking software, similar in scope to blogs or FaceBook, using a dynamic web programming 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. Class size: 36
11842 |
CMSC 118 Hapax Legomena and the words we use: Computing for
the Digital Humanities |
Rebecca Thomas |
. . W . . |
3:10pm-4:30pm |
RKC 100 |
N/A |
Cross-listed: Experimental Humanities 2 credits What, if anything, can we learn by applying basic computing to works of literature? In this course, we'll apply techniques from Natural Language Processing (the subdiscipline of computer science that deals with information in text form) to all kinds of texts. We’ll identify hapax legomena (words that appear only once in a given text) and think about whether and when they are significant. We'll see how scholars try to use statistical techniques to approach disputes over authorship. Each student will work alone or with a small group to pose an interesting question about a specific text or corpus and to construct computational tools for beginning to address the question. No prerequisite. Class size: 12
11378 |
CMSC 143 Object-Oriented Programming with Robots |
Sven Anderson Lab: |
M . W . . . . . . F |
10:10am - 11:30 am 10:30am - 12:30 pm |
RKC 107 |
MATC |
Cross-listed: Mind, Brain & Behavior 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: 18
11379 |
CMSC 145 Discrete Math |
Joseph Kirtland |
. T . Th . |
4:40 pm -6:00 pm |
RKC 101 |
MATC |
Discrete mathematics includes those areas of mathematics that are essential to computer science, information theory, combinatorics, and genetics. This course emphasizes creative problem solving, linking language to logic, and learning to read and write proofs. The topics covered include propositional logic, predicate logic, inductive proof, sets, relations, functions, introductory combinatorics and discrete probability. Applications drawn from computation will motivate most topics. Prerequisite: Mathematics 141 or programming experience. Class size: 18
11380 |
CMSC 201 Data Structures |
Robert McGrail Lab: |
. T . Th . . . . . F |
10:10am - 11:30 am 10:30am - 12:30 pm |
RKC 100 |
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
11381 |
CMSC 312 Theory of Computation |
Rebecca Thomas |
. T . Th . |
3:10 pm -4:30 pm |
RKC 101 |
MATC |
Cross-listed: Mind, Brain & Behavior The course will introduce several computational models that have been developed to formalize the notion of an algorithm. It will also discuss in detail several of the primary topics in the theory of computation including the theory of recursive functions, Turing machines, and several undecidable problems such as the Halting problem. Prerequisites: Computer Science 301 and Mathematics 231/ 235. Class size: 16
11841 |
CMSC 352 Biologically Inspired Machine Learning |
Sven Anderson |
. T . Th . |
10:10am-11:30am |
RKC 107 |
MATC |
In this course, we will examine computation as a metaphor for understanding adaptive systems. We will study several biological systems and relate them to abstract models that incorporate elements of their data structures, information processing, and learning. Neuron models, neural networks, and evolutionary learning will be studied using mathematics and computer simulation. This course emphasizes information processing, pattern recognition, and associated computational abilities of artificial models, but takes an ethological approach to understanding how natural and artificial intelligent systems adapt to their environment. No background in biology is assumed. Prerequisites: Calculus I and Computer Science II. Class size: 15