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CMSC Computer Science( Computer, Mathematical and Physical Sciences) CMSC102 Introduction to Information Technology; (3 credits) Grade Method: REG/P-F. CORE Interdisciplinary & Emerging Issues (IE) Course.For non-majors only. Not recommended for BMGT students. Not open to students who have completed CMSC106, CMSC114, CMSC132 or CMSC214. Credit will be granted for only one of the following: CMSC102, CMSC132 or CMSC214. If CMSC102 is taken before CMSC132 or CMSC214, then credit will be granted for both. An introduction to computer terminology and concepts of computing and information technology. Hands-on experience with a variety of tools available to access the Internet, to find information, as well as PC applications such as a word processor and a spreadsheet package. Students will work in multiple environments (for example, both Windows and UNIX). CMSC106 (PermReq) Introduction to C Programming; (4 credits) Grade Method: REG/P-F. Prerequisite: permission of department. Pre- or corequisite: MATH140. Only for CMPS, ENCP and students with major code: 2299F. Not open to students who have completed CMSC114 or higher. Design and analysis of programs in C. An introduction to computing using structured programming concepts. For further information contact the Undergraduate Education Office, Computer Science Department. CMSC131 (PermReq) Object-Oriented Programming I; (4 credits) Grade Method: REG/P-F. Corequisite: MATH140 and permission of department. Not open to students who have completed CMSC114. Introduction to programming and computer science. Emphasizes understanding and implementation of applications using object-oriented techniques. Develops skills such as program design and testing as well as implementation of programs using a graphical IDE. Programming done in Java. For CMSC majors only. CMSC131H (PermReq) Object-Oriented Programming I; (4 credits) Grade Method: REG/P-F. Corequisite: MATH140 and permission of department. Not open to students who have completed CMSC114. For general honors students only. CMSC132 (PermReq) Object-Oriented Programming II; (4 credits) Grade Method: REG/P-F. Prerequisite: CMSC131 with a grade of C or better; or a score of 5 on the A Java AP exam; or a score of 4 or 5 on the AB Java AP exam; or permission of the department based on satisfactory performance on the department placement exam and permission of department. Corequisite: MATH141. Introduction to use of computers to solve problems using software engineering principles. Design, build, test, and debug medium -size software systems and learn to use relevant tools. Use object-oriented methods to create effective and efficient problem solutions. Use and implement application programming interfaces (APIs). Programming done in Java. CMSC132H (PermReq) Object-Oriented Programming II; (4 credits) Grade Method: REG/P-F/AUD. Prerequisite: CMSC131 with a grade of C or better; or a score of 5 on the A Java AP exam; or a score of 4 or 5 on the AB Java AP exam; or permission of the department based on satisfactory performance on the department placement exam and permission of department. Corequisite: MATH141. For general honors students only. CMSC198A (PermReq) Special Topics in Computer Science for Non-Majors: Special Topics for Non-Computer Science Majors; (1-4 credits) Grade Method: REG/P-F/AUD. Individual Instruction course: contact department or instructor to obtain section number. CMSC212 (PermReq) Introduction to Low-Level Programming Concepts; (4 credits) Grade Method: REG/P-F/AUD. Prerequisite: CMSC132 with a grade of C or better; or permission of the department based on satisfactory performance on the department placement exam and permission of department. Corequisite: CMSC250. Introduction to many of the concepts that lie behind software, such as hardware, memory layout, memory management, and operating systems. Explain how these concepts affect the design of software systems. CMSC250 (PermReq) Discrete Structures; (4 credits) Grade Method: REG. Prerequisite: CMSC131 with a grade of C or better; MATH141; and permission of department. Formerly CMSC 150. Fundamental mathematical concepts related to computer science, including finite and infinite sets, relations, functions, and propositional logic. Introduction to other techniques, modeling and solving problems in computer science. Introduction to permutations, combinations, graphs, and trees with selected applications. CMSC250H Discrete Structures; (4 credits) Grade Method: REG. Prerequisite: CMSC131 with a grade of C or better; MATH141; and permission of department. Formerly CMSC 150. CMSC297 Honors Seminar; (1 credit) Grade Method: S-F. An introduction to the breadth of computer science research. Intended for all Computer Science Honors students, especially those considering a career in research. Will cover work from some of the key figures in the history of computer science, as well as research being pursued at Maryland. CMSC298A (PermReq) Special Topics in Computer Science; (1-4 credits) Grade Method: S-F. Individual Instruction course: contact department or instructor to obtain section number. CMSC298B Special Topics in Computer Science: Bits and Bytes of Computer Science; (1 credit) Grade Method: S-F. Restricted to first time freshmen and first time transfer Computer Science majors. CMSC311 (PermReq) Computer Organization; (3 credits) Grade Method: REG. Prerequisite: CMSC212 and CMSC250 each with a grade of C (2.0) or better; and permission of department. Introduction to assembly language. Design of digital logic circuits. Organization of central processors, including instruction sets, register transfer operations, control microprogramming, data representation, and arithmetic algorithms. Memory and input/output organization. CMSC330 (PermReq) Organization of Programming Languages; (3 credits) Grade Method: REG. Prerequisite: CMSC212 and CMSC250: each with a grade of C (2.0) or better; and permission of department. The semantics of programming languages and their run-time organization. Several different models of languages are discussed, including procedural (e.g., C, Pascal), functional (e.g., ML, LISP), rule-based (e.g., Prolog), and object-oriented (e.g., C++, Smalltalk). Run-time structures, including dynamic versus static scope rules, storage for strings, arrays, records, and object inheritance are explored. CMSC351 (PermReq) Algorithms; (3 credits) Grade Method: REG. Prerequisite: CMSC212 and CMSC250: each with a grade of C (2.0) or better; and permission of department. CMSC351 may not count as one of the required upper level CMSC courses for students who are required to have 24 upper level CMSC credits for graduation, i.e. for students who became computer science majors prior to Fall, 2002. Credit will be granted for only one of the following: CMSC251 or CMSC351. Formerly CMSC 251. A systematic study of the complexity of some elementary algorithms related to sorting, graphs and trees, and combinatorics. Algorithms are analyzed using mathematical techniques to solve recurrences and summations. CMSC390 (PermReq) Honors Paper; (3 credits) Grade Method: REG. Individual Instruction course: contact department or instructor to obtain section number. Prerequisite: admission to CMSC Honors Program. Special study or research directed toward preparation of honors paper. CMSC411 Computer Systems Architecture; (3 credits) Grade Method: REG. Prerequisite: A grade of C or better in (CMSC311 or ENEE350) and a grade of C or better in CMSC330; and permission of department; or CMSC graduate student. Input/output processors and techniques. Intra-system communication, buses, caches. Addressing and memory hierarchies. Microprogramming, parallelism, and pipelining. CMSC412 Operating Systems; (4 credits) Grade Method: REG. CORE Capstone (CS) Course. Prerequisites: A grade of C or better in (CMSC311 or ENEE350) and a grade of C or better in CMSC330; and permission of department; or CMSC graduate student. An introduction to batch systems, spooling systems, and third-generation multiprogramming systems. Description of the parts of an operating system in terms of function, structure, and implementation. Basic resource allocation policies. CMSC414 (PermReq) Computer and Network Security; (3 credits) Grade Method: REG. Prerequisite: A grade of C or better in (CMSC311 or ENEE350) and a grade of C or better in CMSC330; and permission of department; or CMSC graduate student. An introduction to the topic of security in the context of computer systems and networks. Identify, analyze, and solve network-related security problems in computer systems. Fundamentals of number theory, authentication, and encryption technologies, as well as the practical problems that have to be solved in order to make those technologies workable in a networked environment, particularly in the wide-area Internet environment. CMSC417 Computer Networks; (3 credits) Grade Method: REG. Prerequisite: A grade of C or better in CMSC351, a grade of C or better in (CMSC311 or ENEE350), and a grade of C or better in CMSC330; and permission of department; or CMSC graduate student. Computer networks and architectures. The OSI model including discussion and examples of various network layers. A general introduction to existing network protocols. Communication protocol specification, analysis, and testing. CMSC420 Data Structures; (3 credits) Grade Method: REG. Prerequisites: A grade of C or better in CMSC330 and in CMSC351; and permission of department; or CMSC graduate student. Description, properties, and storage allocation of data structures including lists and trees. Algorithms for manipulating structures. Applications from areas such as data processing, information retrieval, symbol manipulation, and operating systems. CMSC421 Introduction to Artificial Intelligence; (3 credits) Grade Method: REG. Prerequisites: A grade of C or better in CMSC330 and in CMSC351; and permission of the department or CMSC graduate student. Areas and issues in artificial intelligence, including search, inference, knowledge representation, learning, vision, natural languages, expert systems, robotics. Implementation and application of programming languages (e.g. LISP, PROLOG, SMALLTALK), programming techniques (e.g. pattern matching, discrimination networks) and control structures (e.g. agendas, data dependencies). CMSC424 Database Design; (3 credits) Grade Method: REG. CORE Capstone (CS) Course. Prerequisite: CMSC420 with a grade of C or better; and permission of department; or CMSC graduate student. Motivation for the database approach as a mechanism for modeling the real world. Review of the three popular data models: relational, network, and hierarchical. Comparison of permissible structures, integrity constraints, storage strategies, and query facilities. Theory of database design logic. CMSC427 Computer Graphics; (3 credits) Grade Method: REG. Prerequisites: MATH240; and a grade of C or better in CMSC420; and permission of department; or CMSC graduate student. An introduction to the principles of computer graphics. Includes an introduction to graphics displays and systems. Introduction to the mathematics of affine and projective transformations, perspective, curve and surface modeling, algorithms for hidden-surface removal, color models, methods for modeling illumination, shading, and reflection. CMSC433 Programming Language Technologies and Paradigms; (3 credits) Grade Method: REG. Prerequisite: CMSC330; and permission of department; or CMSC graduate student. Programming language technologies (e.g., object-oriented programming), their implementations and use in software design and implementation. CMSC434 Introduction to Human-Computer Interaction; (3 credits) Grade Method: REG. Prerequisites: CMSC330 with a grade of C or better and PSYC100; and permission of department; or CMSC graduate student. Assess usability by quantitative and qualitative methods. Conduct task analyses, usability tests, expert reviews, and continuing assessments of working products by interviews, surveys, and logging. Apply design processes and guidelines to develop professional quality user interfaces. Build low-fidelity paper mockups, and a high-fidelity prototype using contemporary tools such as graphic editors and a graphical programming environment (eg: Visual Basic, Java). CMSC435 Software Engineering; (3 credits) Grade Method: REG. CORE Capstone (CS) Course. Prerequisites: (CMSC412, CMSC417, CMSC420, CMSC430, or CMSC433) with a grade of C or better and permission of department; or CMSC graduate student. State-of-the-art techniques in software design and development. Laboratory experience in applying the techniques covered. Structured design, structured programming, top-down design and development, segmentation and modularization techniques, iterative enhancement, design and code inspection techniques, correctness, and chief-programmer teams. The development of a large software project. CMSC451 Design and Analysis of Computer Algorithms; (3 credits) Grade Method: REG. Prerequisite: a grade of C or better in CMSC351; and permission of department; or CMSC graduate student. Fundamental techniques for designing efficient computer algorithms, proving their correctness, and analyzing their complexity. General topics include sorting, selection, graph algorithms, and basic algorithm design paradigms (such as divide-and-conquer, dynamic programming and greedy algorithms), lower bounds and NP-completeness. CMSC456 Cryptology; (3 credits) Grade Method: REG. Prerequisites: Any two 400-level MATH courses; or CMSC330 and CMSC351; and permission of department; or CMSC graduate student. Also offered as MATH456. Credit will be granted for only one of the following: CMSC456 or MATH456. Importance in protecting data in communications between computers. The subject lies on the border between mathematics and computer science. Mathematical topics include number theory and probability, and computer science topics include complexity theory. CMSC460 Computational Methods; (3 credits) Grade Method: REG. Prerequisites: MATH240; and MATH241; and CMSC106 or CMSC114 or ENEE114; and permission of department; or CMSC graduate student. Also offered as AMSC460. Credit will be granted for only one of the following: AMSC/CMSC/MAPL460 or AMSC/CMSC/MAPL466. Basic computational methods for interpolation, least squares, approximation, numerical quadrature, numerical solution of polynomial and transcendental equations, systems of linear equations and initial value problems for ordinary differential equations. Emphasis on methods and their computational properties rather than their analytic aspects. Intended primarily for students in the physical and engineering sciences. CMSC466 Introduction to Numerical Analysis I; (3 credits) Grade Method: REG. Prerequisites: MATH240; and MATH241; and CMSC106 or CMSC114 or ENEE114; and permission of department; or CMSC graduate student. Also offered as AMSC466. Credit will be granted for only one of the following: AMSC/CMSC/MAPL460 or AMSC/CMSC/MAPL466. Floating point computations, direct methods for linear systems, interpolation, solution of nonlinear equations. CMSC498A (PermReq) Selected Topics in Computer Science; (1-3 credits) Grade Method: REG. Individual Instruction course: contact department or instructor to obtain section number. CMSC498M (PermReq) Selected Topics in Computer Science: Game Programming; (3 credits) Grade Method: REG. Prerequisite: permission of department. Corequisite: CMSC427 or permission of instructor. CMSC498P (PermReq) Selected Topics in Computer Science: Industrial Practices Apprenticeship; (1 credit) Grade Method: REG. Co-requisite: CMSC 435. CMSC498Q (PermReq) Selected Topics in Computer Science: Advanced Industrial Practices; (1-3 credits) Grade Method: REG. CMSC498Z (PermReq) Selected Topics in Computer Science: Software Project Management; (3 credits) Grade Method: REG/P-F/AUD. CMSC499A (PermReq) Independent Undergraduate Research; (1-3 credits) Grade Method: REG/P-F/AUD. Individual Instruction course: contact department or instructor to obtain section number. CMSC598 (PermReq) Practical Training; (1 credit) Grade Method: S-F. Individual Instruction course: contact department or instructor to obtain section number. CMSC631 Program Analysis and Understanding; (3 credits) Grade Method: REG/AUD. Prerequisite: CMSC 430 or equivalent. Techniques for static analysis of source code and modern programming paradigms. Analysis techniques: data flow analysis, program dependence graphs, program slicing, abstract interpretation. The meaning of programs: denotational semantics, partial evaluation. Advanced treatment of abstraction mechanisms: polymorphic types, operation overloading, inheritance, object-oriented programming and ML-like programming languages. CMSC634 Empirical Research Methods for Computer Science; (3 credits) Grade Method: REG/AUD. Prerequisite: Computer Science graduate student or permission of instructor. Recommended: Introductory statistics class. Credit will be granted for only one of the following: CMSC838G (Fall 2005) or CMSC634. A graduate-level introductory course on empirical reseach methods for computer scientists. Experimental techniques for evaluating software systems and processes, human performance using interfaces, programming environments, and software engineering methods. Introduction to constructs and methods of measurements, qualitative and quantitative design, quasi-experimental and non-experimental design, baseline design, and statistical analysis. CMSC652 Complexity Theory; (3 credits) Grade Method: REG/AUD. Prerequisite: CMSC451 or CMSC452; or permission of instructor. Credit will be granted for only one of the following: CMSC652 or CMSC858G. Formerly CMSC 858G. This course will define what it means for a problem to be hard (or easy) in a variety of ways. The emphasis will be on natural problems. Topics may include NP-completeness, Sparse Sets, Graph Isomoprhism (why it is thought to not be NP-complete), Counting problems, and approximation problems. CMSC660 (PermReq) Scientific Computing I; (3 credits) Grade Method: REG/AUD. Prerequisite: AMSC/CMSC/MAPL 460 or AMSC/CMSC/MAPL 466, or knowledge of basic numerical analysis (linear equations, nonlinear equations, integration, interpolation) with permission of instructor. Knowledge of C or Fortran. Also offered as AMSC 660. Credit will be granted for only one of the following: AMSC 660, CMSC 660 or MAPL 660. Monte Carlo simulation, numerical linear algebra, nonlinear systems and continuation method, optimization, ordinary differential equations. Fundamental techniques in scientific computation with an introduction to the theory and software for each topic. CMSC662 Computer Organization and Programming for Scientific Computing; (3 credits) Grade Method: REG. Prerequisite: AMSC/CMSC/MAPL 460, AMSC/CMSC/MAPL 466 or knowledge of basic numerical analysis (linear equations, nonlinear equations, integration, interpolation) with permission of instructor. Knowledge of C or Fortran. Also offered as AMSC 662. Credit will be granted for only one of the following: AMSC 662 or CMSC 662. This course presents fundamentals issues of computer hardware, software, parallel computing, and scientific data management for programming for scientific computation. CMSC663 Advanced Scientific Computing I; (3 credits) Grade Method: REG. Also offered as AMSC663. CMSC666 Numerical Analysis I; (3 credits) Grade Method: REG/AUD. Prerequisites: AMSC/CMSC/MAPL 466; and MATH 410. Also offered as AMSC 666. Credit will be granted for only one of the following: AMSC 666, CMSC 666 or MAPL 666. Iterative methods for linear systems, piecewise interpolation, eigenvalue problems, numerical integration. CMSC711 Computer Networks; (3 credits) Grade Method: REG/AUD. Prerequisite: CMSC 412 or equivalent. Priciples, design, and performance evaluation of computer networks. Network architectures including the ISO model and local area networks (LANs). Communication protocols and network topology. CMSC714 High Performance Computing Systems; (3 credits) Grade Method: REG/S-F. Prerequisites: (CMSC411 and CMSC412) or permission of instructor. Slected topics in high-performance systems, including contemporary architectures, interconnection topologies, shared memory and message-passing systems, multi-threaded kernels, latency avoidance and hiding techniques, methods for data and workload partitioning performance profiling, debugging. CMSC723 Computational Linguistics I; (3 credits) Grade Method: REG/AUD. Prerequisite: CMSC421 or equivalent; or permission of instructor. PhD Comp credit for CMSC723 or CMSC823, not both. Also offered as LING723. Not open to students who have completed LING645. Fundamental methods in natural language processing. Topics include: finite-state methods, context-free and extended context-free models of syntax; parsing and semantics interpretation; n-gram and Hidden Markov models, part-of-speech tagging; natural language applications such as machine translation, automatic summarization, and question answering. CMSC726 Machine Learning; (3 credits) Grade Method: REG/AUD. Prerequisite: CMSC 421 or equivalent or permission of instructor. Reviews and analyzes both traditional symbol-processing methods and genetic algorithms as approaches to machine learning. (Neural network learning methods are primarily covered in CMSC 727.) Topics include induction of decision trees and rules, version spaces, candidate elimination algorithm, exemplar-based learning, genetic algorithms, evolution under artificial selection of problem-solving algorithms, system assessment, comparative studies, and related topics. CMSC733 Computer Processing of Pictorial Information; (3 credits) Grade Method: REG/AUD. Prerequisite: CMSC 420. Input, output, and storage of pictorial information. Pictures as information sources, efficient encoding, sampling, quantization, approximation. Position-invariant operations on pictures, digital and optical implementations, the pax language, applications to matched and spatial frequency filtering. Picture quality, image enhancement and image restoration. Picture properties and pictorial pattern recognition. Processing of complex pictures; figure extraction, properties of figures. Data structures for pictures description and manipulation; picture languages. Graphics systems for alphanumeric and other symbols, line drawings of two- and three-dimensional objects, cartoons and movies. CMSC760 Advanced Linear Numerical Analysis; (3 credits) Grade Method: REG/AUD. Prerequisite: AMSC/CMSC/MAPL 666 or permission of instructor. Also offered as AMSC 600. Credit will be granted for only one of the following: AMSC 600, CMSC760 or MAPL 760. Formerly CMSC 770. Advanced topics in numerical linear algebra, such as dense eigenvalue problems, sparse elimination, iterative methods, and other topics. CMSC798 (PermReq) Graduate Seminar in Computer Science; (1-3 credits) Grade Method: REG/AUD. Individual Instruction course: contact department or instructor to obtain section number. CMSC798A (PermReq) Graduate Seminar in Computer Science; (1-3 credits) Grade Method: REG/AUD. Individual Instruction course: contact department or instructor to obtain section number. CMSC majors only. Other majors require permission of department. CMSC799 (PermReq) Master's Thesis Research; (1-6 credits) Grade Method: REG/S-F. Individual Instruction course: contact department or instructor to obtain section number. CMSC818A (PermReq) Advanced Topics in Computer Systems; (1-3 credits) Grade Method: REG/AUD. Individual Instruction course: contact department or instructor to obtain section number. CMSC818K Advanced Topics in Computer Systems: Distributed Systems; (3 credits) Grade Method: REG/AUD. CMSC828A (PermReq) Advanced Topics in Information Processing; (1-3 credits) Grade Method: REG/AUD. Individual Instruction course: contact department or instructor to obtain section number. CMSC828C Advanced Topics in Information Processing: Statistical and Neural Pattern Recognition; (1-3 credits) Grade Method: REG/AUD. CMSC828K Advanced Topics in Information Processing: Sensors and Mobile Data Tracking; (3 credits) Grade Method: REG/AUD. CMSC828N Advanced Topics in Information Processing: Computational Gene Finding and Genome Assembly; (3 credits) Grade Method: REG/AUD. CMSC838A (PermReq) Advanced Topics in Programming Languages; (1-3 credits) Grade Method: REG/AUD. Individual Instruction course: contact department or instructor to obtain section number. CMSC838K Advanced Topics in Programming Languages: How to do Research; (1 credit) Grade Method: REG/AUD. CMSC858A (PermReq) Advanced Topics in Theory of Computing; (1-3 credits) Grade Method: REG/AUD. Individual Instruction course: contact department or instructor to obtain section number. CMSC858B Advanced Topics in Theory of Computing: Error Correcting Codes; (3 credits) Grade Method: REG/AUD. CMSC858K Advanced Topics in Theory of Computing: Combinatorial Optimization; (3 credits) Grade Method: REG/AUD. Click here for more course information. CMSC858L Advanced Topics in Theory of Computing: Graphs and Networks in Computational Biology; (3 credits) Grade Method: REG/AUD. CMSC878A (PermReq) Advanced Topics in Numerical Methods; (1-3 credits) Grade Method: REG/AUD. Individual Instruction course: contact department or instructor to obtain section number. CMSC898 Pre-Candidacy Research; (1-8 credits) Grade Method: REG/S-F. Individual Instruction course: contact department or instructor to obtain section number. CMSC899 (PermReq) Doctoral Dissertation Research; (6 credits) Grade Method: REG/S-F. Individual Instruction course: contact department or instructor to obtain section number.
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