Curriculum
Courses
Faculty

• CSCI-A 504 Introductory C++ Programming (2 cr.)P: Programming experience. Topics include aspects of C++ that are not object-oriented, basic data structures, standard libraries, and Unix tools for project management. Credit not given for both A504 and either A304, A597, A592, C212, H212, or BUS K201. Program is not currently offering this course.  
• CSCI-A 506 Object-Oriented Programming in C++ (2 cr.)P: Either A201, A304, A504, or A597. Topics include objects, classes, encapsulation, inheritance, polymorphism, templates, and ex­ceptions. Credit not given for both A506 and either A306, A202, A592, A598, C212, or H212. Program is not currently offering this course.  
• CSCI-A 521 Computing Tools for Scientific Research (3 cr.)C: Math 118 or higher required; Math M211 recommended. Introduc­tion to computer-based tools useful for analysis and under­standing of scientific data. Basic methods of computation, data processing, and display in systems such as Matlab combined with elementary practical C/C++ programming. Techniques to support customized scientific research tasks, with particular emphasis on biological, neural, and behavioral sciences. Lec­ture and laboratory.  
• CSCI-A 538 Network Technologies and Administration (3 cr.)P: A110, EDUC W200, or equivalent computer literacy. Introduc­tion to network principles and current network technology, both hardware and software. Network administration tools and techniques. Laboratory provides practical experience. Credit not given for both A538 and A338.  
• CSCI-A 546 User-Interface Programming (3 cr.)P: Either A201, A202, A306, C212, A506, A597, A598, or equivalent experience. Learn to prototype and build graphical user interfaces for computer applications. Contemporary software design methodology. Students design and implement prototype interfaces to appli­cations provided by the instructor. Extensive use will be made of both commercial and experimental software tools. Lab fee. Credit not given for both A546 and A346. Program is not currently offering this course.  
• CSCI-A 548 Mastering the World Wide Web (3 cr.)P: Two semesters of programming experience or equivalent, and some knowl­edge of operating systems. Project-oriented course leading to ability to maintain a Web site with full functionality. Topics in­clude background on Internet network protocols and program­ming, Web server administration, advanced Web design and authoring, Web protocols, interfacing services into the Web. Lab fee. Credit not given for both A548 and A348.  
• CSCI-A 590 Topics in Programming (1-2 cr.)Eight-week courses de­signed to provide foundations for using modern programming tools for applications and web development. Lecture and lab. May be repeated for a maximum of six credits.
• CSCI-A 591 Introduction to Computer Science (3 cr.)A first course in computer science for those intending to take advanced computer science courses. Introduction to programming and to algorithm design and analysis. Using the Scheme programming language, the course covers several programming paradigms. Lecture and laboratory. Credit not given for both A591 and C211. 
• CSCI-A 592 Introduction to Software Systems (3 cr.)P: Programming experience. Design of computer software systems and intro­duction to programming. Topics include the C++ programming language and its data structure facilities; building and maintain­ing large projects; shell tools, and system calls. Introduction to object-oriented programming. Lecture and laboratory. Credit not given for both A592 and C212. 
• CSCI-A 593 Computer Structures (3 cr.)P: A592. Structure and in­ternal operation of computers. The architecture and assembly language programming of a specific computer are stressed, in addition to general principles of hardware organization and low-level software systems. Lecture and laboratory. Lab fee. Credit not given for both A593 and C335. May be applied toward the Ph.D. minor. 
• CSCI-A 594 Data Structures (3 cr.)P: A592. P or C: C241 and A593. Systematic study of data structures encountered in computing problems; structure and use of storage media; methods of rep­resenting structured data; and techniques for operating on data structures. Lecture and laboratory. Credit not given for both A594 and C343. May be applied toward the Ph.D. minor. 
• CSCI-A 595 Fundamentals of Computing Theory (3 cr.)P: C241. P or C: C212. Fundamentals of formal language theory, computation models and computability, the limits of computability and feasi­bility, and program verification. Credit not given for both A595 and B401. May be applied toward the Ph.D. minor, graduate credit available for CS M.S. candidates with special permission. 
• CSCI-A 596 Programming Languages (3 cr.)P: A594. Systematic approach to programming languages. Relationships among languages, properties and features of languages, and the com­puter environment necessary to use languages. Lecture and laboratory. Credit not given for both A596 and C311. May be applied toward the Ph.D. minor. 
• CSCI-A 597 Introduction to Programming I (3 cr.)Fundamental pro­gramming constructs, including loops, arrays, classes, and files. General problem-solving techniques. Emphasis on modular programming, user-interface design, and developing good pro­gramming style. Credit not given for both A597 and A201. 
• CSCI-A 598 Introduction to Programming II (1.5-3 cr.)P: A597, A201, A504, or A304. Advanced programming techniques: user-defined functions and types, recursion vs iteration, parameter-passing mechanisms. Classic abstract data types and algorithms. Programming style. Object-oriented programming. Web programming. May be taught full term or 8 week. Credit not given for both A598 and CSCI-A 202. May be repeated for credit up to 3 hrs. 
• CSCI-B 403 Introduction to Algorithm Design and Analysis (3 cr.)Credit not given for both B403 and B503. 
• CSCI-B 441 Digital Design (4 cr.)Credit not given for both B441 and B541. Not applicable toward a major in computer science. 
• CSCI-B 443 Introduction to Computer Architecture (3 cr.)Credit not given for both B443 and B543. 
• CSCI-B 501 Theory of Computing (3 cr.)P: C241. Deterministic and nondeterministic automata, regular expressions, pumping lemmas; context-free languages, parsing, pushdown automata, context-sensitive languages, LBA, LR(k) languages, closure and decidability of language classes. Turing machines, random ac­cess machines, grammars, general recursive functions, equiva­lence of computation models, universal machines, relative computing. Unsolvability, semi-recursive sets, Rice’s Theorem. Space and time complexity, NP completeness. 
• CSCI-B 502 Computational Complexity (3 cr.)Study of computational complexity classes, their intrinsic properties, and relations between them. Topics include time and space computational complexity, reducibility and completeness of problems within complexity classes, complexity of optimization problems, com­plexity hierarchies, relativization of the P=?NP conjecture, and parallel computation models and the class NC. 
• CSCI-B 503 Algorithms Design and Analysis (3 cr.)P: MATH M216, and C343. Models, algorithms, recurrences, summations, growth rates. Probabilistic tools, upper and lower bounds; worst-case and average-case analysis, amortized analysis, dynamization. Comparison-based algorithms: search, selection, sorting, hashing. Information extraction algorithms (graphs, databases). Graphs algorithms: spanning trees, shortest paths, connectivity, depth—first search, breadth—first search. 
• CSCI-B 504 Introduction to Cryptography (3 cr.)Familiar with basic algebra, combinatorics and probability theory recommended. The course provides students with a foundational introduction to cryptography. Students learn the basic primitives used in cryptography such as symmetric encryption, public-key encryption, message authentication codes, digital signatures, cryptographic hashes and related material. Computational aspects of modern cryptography are stressed, as are appropriate security models, and computational security reductions. 
• CSCI-B 505 Applied Algorithms (3 cr.)The course studies the design, implementation, and analysis of algorithms and data structures as applied to real world problems. The topics include divide-and-conquer, optimization, and randomized algorithms applied to problems such as sorting, searching, and graph analysis. The course teaches trees, hash tables, heaps, and graphs.  

• CSCI-B 510 Introduction to Applied Logic (3 cr.)Structures: relations between structures, term structures. Description: notation and meaning, substitution operations, first order formulas, database languages, program verification conditions, semantic valuation, normal forms, quantifier reduction, axiomatic theo­ries. Proof: resolution, sequential calculi, natural deduction, automated theorem proving, semantic completeness. Limits of formalization: compactness, undecidability of truth, undecid­ability of canonical theories, nonformalizability of database theory. 
• CSCI-B 521 Programming Language Principles (3 cr.)Systematic approach to programming languages. Relationships among languages, properties and features of languages, the computer environment necessary to support language execution. 
• CSCI-B 522 Programming Language Foundations (3 cr.)P: C311 or B521, and B510. Introduction to denotational, operational, and axiomatic approaches to programming language semantics. Semantic analysis of major programming language features. Logics of programs. 
• CSCI-B 524 Parallelism in Programming Languages and Systems (3 cr.)P: P436 or P536, and either C311, H311 or B521, C343 or H343. Fundamentals of parallel computation, with an emphasis on parallel programming methodology and programming lan­guages. Topics include: parallel algorithms; major paradigms for parallel software construction; (data parallelism, task/thread parallelism and CSP); compiling programs for parallel comput­ers. 
• CSCI-B 534 Distributed Systems (3 cr.)A balanced treatment of fundamentals and practice of distributed systems. The founda­tional models, algorithms, and principles upon which distrib­uted systems are based are studied in detail. These fundamen­tals are placed in the context of practical implementations by means of reading and critical analysis of research papers. 
• CSCI-B 541 Hardware System Design I (3 cr.)P: C335 or honors ver­sion. Structured approach to hardware design, emphasizing hardwired and microprogrammed control. Boolean algebra, hardware building blocks, architecture and control, imple­mentation issues. In the laboratory, students build a working computer using hardware prototyping technologies. Basic train­ing in the use of design and simulation software. Lecture and laboratory. 
• CSCI-B 543 Computer Architecture (3 cr.)P: C335 and C343 or honors versions. Fundamentals of computer design, instruc­tion processing and performance analysis. Architecture of single-processor systems, focusing on pipelining, memory and memory hierarchies, and interconnect technology. Exploration of architecture classes such as high-performance multiproces­sors, massively parallel computers, embedded systems. 
• CSCI-B 544 Security for Networked Systems (3 cr.)This course is an extensive survey of system and network security. Course materials cover the threats to information confidentiality, integrity and availability and the defense mechanisms that control such threats. The course provides the foundation for more advanced security courses and hands-on experiences through course projects.
• CSCI-B 546 Malware Epidemic: Threat and Defense (3 cr.)One semester of programming or equivalent recommended. This course looks at systems and protocols, how to design threat models for them and how to use a large number of current security technologies and concepts to block specific vulnerabilities. Students will use a large number of systems and programming security tools in the laboratories. 
• CSCI-B 547 Systems and Protocol Security and Information Assurance (3 cr.)Some previous programming background and general computer networking and operating systems literacy recommended. This course covers the design and analysis of secure systems, including identifying security goals and risks, threat modeling, defense, integrating different technologies to achieve security goals, developing security protocols and policies, implementing security protocols and secure coding. Some real world scenarios that have many security requirements will be studied. 
• CSCI-B 548 Privacy in Pervasive Computing (3 cr.)This course prepares graduate students towards a successful research career in wearable and sensor-based computing. This course combines both lectures on the research process and student-led round-table discussions of seminal and influential papers in the field. 

• CSCI-B 551 Elements of Artificial Intelligence (3 cr.)P: C343 or H343, good knowledge of LISP or Scheme. Introduction to major is­sues and approaches in artificial intelligence. Principles of reac­tive, goal-based, and utility-based agents. Problem-solving and search. Knowledge representation and design of representa­tional vocabularies. Inference and theorem proving, reasoning under uncertainty, planning. Overview of machine learning. 
• CSCI-B 552 Knowledge Based Artificial Intelligence (3 cr.)P: B551. Knowledge-based methods for artificial intelligence systems: knowledge representation, organization, and application. Typical content includes principles of memory organization, indexing and retrieval. Memory-based, analogical, and case-based reasoning. Applications to understanding, explanation, planning, and advisory systems. 
• CSCI-B 553 Neural and Genetic Approaches to Artificial Intelligence (3 cr.)P: CSCI-B 551. Approaches to the design of intelligent systems inspired by nervous systems, evolution, and animal be­havior. Distributed and perceptually-grounded representations. Temporal processing. Perception and action. Genetic search. Unsupervised and reinforcement learning. Comparison of sym­bolic, subsymbolic, and hybrid approaches to intelligence. 
• CSCI-B 554 Probabilistic Approaches to Artificial Intelligence (3 cr.)CSCI-B 403, MATH-M 301 and MATH-M 365 recommended. Theory and practice of computational and mathematical foundations of probabilistic models for artificial intelligence and other areas of computing. Topics include: random variables and independence; graphical models including Bayesian and Markov networks; exact and approximate inference algorithms; constrained, unconstrained and stochastic optimization algorithms; parameter and structure estimation; temporal models; applications. 

• CSCI-B 555 Machine Learning (3 cr.)Theory and practice of constructing algorithms that learn functions and choose optimal decisions from data and knowledge. Topics include: mathematical/probabilistic foundations, MAP classification/regression, linear and logistic regression, neural networks, support vector machines, Bayesian networks, tree models, committee machines, kernel functions, EM, density estimation, accuracy estimation, normalization, model selection. 
• CSCI-B 557 Music Information Processing: Audio (3 cr.)This course discusses music analysis and processing problems that use sampled audio as the primary data representation. Digital signal processing is discussed, along with filtering and its relationship to Fourier techniques. Applications considered include score following, automatic music transcription and annotation from audio, musical accompaniment systems, and audio effects. 

• CSCI-B 561 Advanced Database Concepts (3 cr.)P: C241, C335, and C343 or honors versions. Database models and systems, espe­cially relational and object-oriented; relational database design theory; structures for efficient data access; query languages and processing; database applications development; views. Transaction management: concurrency and recovery. 
• CSCI-B 563 Bioinformatics Algorithms (3 cr.)Basic undergraduate algorithms and one programming class or equivalent programming experience in C/C++, Java, or Python recommended. No biology background will be assumed. This course is on algorithmic techniques for solving problems in molecular biology, genetics and genomics. It covers basic algorithmic/combinatorial optimization techniques for alignment, mapping, search and assembly of genomes, resolving mapping ambiguity and genotyping, modeling evolution of genomes (e.g. cancer genomes) and detecting structure and interaction partners of biomolecules.
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• CSCI-B 565 Data Mining (3 cr.)Algorithmic and practical aspects of discovering patterns and relationships in large databases. The course also provides hands-on experience in data analysis, clustering and prediction. Topics include: data preprocessing and exploration, data warehousing, association rule mining, classification and regression, clustering, anomaly detection, human factors and social issues in data mining. 
• CSCI-B 581 Advanced Computer Graphics (3 cr.)P: C343, MATH M301 or M303, or equivalent experience. Introduction to graphics hardware and software. Two-dimensional graphics methods, transformations, and interactive methods. Three-di­mensional graphics, transformations, viewing geometry, object modeling and interactive manipulation methods. Basic lighting and shading. Video and animation methods. 
• CSCI-B 582 Image Synthesis (3 cr.)P: B581, MATH M215. Raster image display: color theory, gamma correction, and filtering. Advanced shading methods: local illumination models, global illumination models. Surface display, including ray tracing and Z-buffering. Solid modeling: spline surfaces, CSG, superquad­rics, and deformations. Scientific visualization: isosurfaces and volume rendering. Program is not currently offering this course. 
• CSCI-B 599 Teaching in Computer Science (1 cr.)General principles of teaching and practical experiences that relate to teaching computer science. An important feature of the course is the microteaching, in which each participant prepares and delivers short lectures to the seminar participants. Each presentation is followed by critical analysis and discussion. Program is not currently offering this course. 
• CSCI-B 603 Advanced Algorithms Analysis (3 cr.)P: B503. Advanced topics in analysis of algorithms, including fast algorithms for classical problems, lower bounds results, and statistical behav­ior. 
• CSCI-B 607 Philosophy of Computation (3 cr.)P: Consent of the instructor. Critical examination of the conceptual foundations of computing. Several different views assessed with respect to conceptual, explanatory, and empirical criteria. Primary focus on formal symbol manipulation, recursive function theory, ef­fective computability, computational complexity, digitality, and information processing. Some nonstandard approaches also considered: connectionism, dynamics, and artificial life. Program is not currently offering this course. 
• CSCI-B 609 Topics in Algorithms and Computing Theory (1-6 cr.)P: Instructor’s permission. Special topics in algorithms and computing theory. May be repeated for credit with permission. 
• CSCI-B 619 Topics in Applied Logic (1-6 cr.)P: Instructor’s permission. Special topics in applied logic. May be repeated for credit with permission. 
• CSCI-B 621 Advanced Concepts in Programming Languages (3 cr.)P: Either C311, H311, or B521. P or C: P423 or P523. Discus­sion of current issues in the design of programming languages. Modularity, abstraction, and static analysis. Applicative and nonapplicative models. Single and multiple processing. 
• CSCI-B 622 Programming Language Type Systems (3 cr.)P: C311 or B521. Theoretical foundations and engineering techniques for modern type systems, focusing on polymorphism and sub­typing in typed lambda-calculi; applications, including type systems for objects, abstract data types, and modules; issues in type checker implementation and polymorphic type inference. Program is not currently offering this course. 
• CSCI-B 629 Topics in Programming Languages (1-6 cr.)P: C311 or B521 and instructor’s permission. Special topics in program­ming languages. May be repeated for credit with permission.
• CSCI-B 639 Topics in Software Systems (1-6 cr.)P: Instructor’s permission. Special topics in soft­ware systems. May be repeated for credit with permission.
• CSCI-B 644 Very Large Scale Integration (3 cr.)P: B441 or B541. Basic theory and practice required to convert hardware algorithms and architecture to silicon structures. Use of state-of-the-art design tools for integrated circuits. Lab fee. 
• CSCI-B 649 Topics in Systems (1-6 cr.)P: Instructor’s permission. Spe­cial topics in systems. May be repeated for credit with permission. 
• CSCI-B 651 Natural Language Processing (3 cr.)P: B551. R: B552 or B553. Theory and methods for natural language processing. Al­gorithms for sentence parsing and generation. Context-free and unification grammars. Question-and-answer systems. Analysis of narratives. Finite-state approaches to computational phonol­ogy and morphology. Machine translation. Machine learning of natural language. Speech recognition. Neural-network and statistical alternatives to symbolic approaches. 
• CSCI-B 652 Computer Models of Symbolic Learning (3 cr.)P: B552. Symbolic artificial intelligence methods for learning. Inductive and explanation-based generalization. Failure-driven learning. Case-based learning. Typical content includes operationality of explanations and utility of learning. Goal-driven learning. Cri­teria for when, what, and how to learn. Learning in integrated architectures. 
• CSCI-B 656 Web Mining (3 cr.)Machine learning techniques to mine the Web and other unstructured/semistructured, hypertex­tual, distributed information repositories. Crawling, indexing, ranking and filtering algorithms using text and link analysis. Applications to search, classification, tracking, monitoring, and Web intelligence. Group project on one of the topics covered in class. 
• CSCI-B 657 Computer Vision (3 cr.)P: C463 or B551. Concepts and methods of machine vision as a branch of artificial intelligence. Basics of digital image processing. Local and global tools for deriving information from image data. Model-based object recognition and scene understanding. 
• CSCI-B 659 Topics in Artificial Intelligence (1-6 cr.)P: Instructor’s permission. Special topics in artificial intelligence. May be repeated for credit with permission. 
• CSCI-B 661 Database Theory and Systems Design (3 cr.)P: B461 or B561. Database models: relational, deductive, complex-object, object-oriented. Query languages: relational algebra and calcu­lus, datalog, fixpoint logics, object-oriented query languages. Transaction management theory: concurrency control, recov­ery, distribution. Post-relational and object-oriented database systems. 
• CSCI-B 662 Database Systems and Internal Design (3 cr.)P: CSCI-B 561. This course deals with database management systems and their modern applications. We will discuss various issues to be considered and design decisions to be made in these systems. Topics include storage management, access methods, query processing and optimization strategies, concurrently control techniques, data warehousing, data mining, semi-structured data management, etc. 
• CSCI-B 665 Software Engineering Management I (3 cr.)P: B561 or BUS S560. Topics include the high cost of software, the software life cycle, understanding programming teams, and methodologies for controlling development. Presentation of readings and supervision of programming teams producing software products required. Program is not currently offering this course. 
• CSCI-B 666 Software Management Implementation II (1-3 cr.)P: B665. Continuation of projects from B665. Periodic reports and a final paper required. If taken for two or more credits, an additional project or paper is required. Program is not currently offering this course. 
• CSCI-B 669 Topics in Database and Information Systems (1-6 cr.)P: Instructor’s permission. Special topics in database and infor­mation systems. May be repeated for credit with permission. 
• CSCI-B 673 Advanced Scientific Computing (3 cr.)P: P573 and MATH M471. Multiprocessor organization: vectorization, memory organization, processor topologies and architectures. Models of parallelism. Programming language and systems for scientific and high-performance computing. Environments for interactive scientific experiments and databases. Distributed programming tools. Parallelism in scientific problems: parallel algorithmic techniques, parallel algorithms and models, parallel perfor­mance analysis and debugging. 
• CSCI-B 679 Topics in Scientific Computing (1-6 cr.)P: Instructor’s permission. Special topics in scientific computing. May be repeated for credit with permission. 
• CSCI-B 689 Topics in Graphics and Human Computer Interaction (1-6 cr.) P: Instructor’s permission. Special topics in graphics and human computer interaction. May be repeated for credit with permission.
• CSCI-P 423 Compilers (4 cr.)Credit not given for both P423 and P523. 
• CSCI-P 436 Introduction to Operating Systems (4 cr.)Credit not given for both P436 and P536. 
• CSCI-P 438 Fundamentals of Computer Networks (3 cr.)Credit not given for both P438 and P538. Not applicable toward a major in computer science. 
• CSCI-P 442 Digital Systems (4 cr.)Credit not given for both P442 and P542. Not applicable toward a major in computer science. Program is not currently offering this course. 
• CSCI-P 515 Specification and Verification (3 cr.)P: C311. Tools and techniques for rigorous reasoning about software and digital hardware. Safety, reliability, security, and other design-critical applications. Decision algorithms. Projects involving the use of automated reasoning, such as model checkers, theorem provers, and program transformation. Credit not given for both P415 and P515. 
• CSCI-P 523 Programming Language Implementation (3 cr.)P: B521 or C311. Implementation of traditional and nontraditional computer programming languages. Compilation, including lexical analysis, parsing, optimization, code generation, and testing. Run-time support, including run-time libraries, storage management, input-output. Comparison of implementation techniques. Extensive laboratory exercises. 
• CSCI-P 532 Object-Oriented Software Development (3 cr.)P: Proficiency in Java. This course will help turn motivated students into superior contributors to any small- to mid-sized commercial or open-source software project.  It takes a hands-on, learning-by-doing approach. Students are introduced to design patterns, tools, and teamwork strategies from the first assignment to the last project. 
• CSCI-P 535 Pervasive Computing (3 cr.)P: Object oriented program­ming. Topics in pervasive computing, such as sensors, mobility, tangibles, ambient displays, middleware, location and context-awareness; user-centered design methods, such as require­ments gathering, design, prototyping, and evaluation. Labs cover current technologies, such as sensors and mobile devices. Lecture and laboratory. Lab fee. 
• CSCI-P 536 Advanced Operating Systems (3 cr.)P: C335 and C343, or honors versions. Advanced topics in operating systems, such as: multitasking, synchronization mechanisms, distributed system architecture, client-server models, distributed mutual exclusion and concurrency control, agreement protocols, load balancing, failure recovery, fault tolerance, cryptography, multiprocessor operating systems. 
• CSCI-P 538 Computer Networks (3 cr.)P: Operating systems or net­working course. Layered TCP/IP architecture. LAN technologies (Ethernet, wireless, token rings). Switching. Internet addressing (IPv4, IPv6). Routing protocols. Congestion control (TCP, UDP). Applications (DNS, HTTP, peer-to-peer networks). Selection of topics including DHCP, ICMP, VPNs, multicast, security. Credit given for only one of P438 and P538. 
• CSCI-P 542 Hardware System Design II (3 cr.)P: B541 or B441. Depending on instructor, a selection of topics in system-level design, such as simulation, logic synthesis, high-level synthesis, codesign, embedded software, verification, test, requirements specification, and others. Projects in system-level design. Computer-aided design tools. Lecture and laboratory. Program is not currently offering this course. 
• CSCI-P 545 Embedded and Real-Time Systems (3 cr.)P: Any 400-level “systems” course (middle digit 3 or 4). Design and implementa­tion of purpose-specific, locally distributed software systems. Models and methods for time-critical applications. Real-time operating systems. Testing, validation, and verification. Safety-critical design. Related topics, such as resiliency, synchroniza­tion, sensor fusion, etc. Lecture and laboratory. 

• CSCI-P 556 Applied Machine Learning (3 cr.) The main aim of the course is to provide skills to apply machine learning algorithms on real applications. We will consider fewer learning algorithms and less time on math and theory and instead spend more time on hands-on skills required for algorithms to work on a variety of data sets.  

• CSCI-P 565-566 Software Engineering I-II (3-3 cr.)P: C343, B461 previously or B561 concurrently. Analysis, design, and imple­mentation of software systems. Requirements specification: data and process modeling. Software design methodologies. Software quality assurance: testing and verification. Software development processes. Program is not currently offering this course. 
• CSCI-P 573 Scientific Computing (3 cr.)P: MATH M303 or M301, M343, and C212 or H212. For students from all scientific, engineering, and mathematical disciplines, this course provides an overview of computer hardware, software, and numeri­cal methods that are useful on scientific workstations and supercomputers. Topics include high-performance computer architectures, software tools and packages, characteristics of numerical methods in common use, graphical presentation of results, and performance analysis and improvement. 
• CSCI-P 632 Object-Oriented Software Management (3 cr.)P: Instructor's permission. This course will help turn motivated students into superior managers of any small- to mid-sized commercial or open-source software project. It takes a hands-on, learning-by-doing approach. Students are introduced to the main management concerns of managing smallish design and development teams. 
• CSCI-Y 790 Graduate Independent Study (1-6 cr.)Independent study under the direction of a faculty member, culminating in a writ­ten report. R grade not allowed. The different options for independent study are: Research and Reading, Software System Development, Master’s Research Project, Master’s Software Project, and a University Master’s Thesis. May be repeated for credit.
• CSCI-Y 798 Professional Practicum/Internship (non-credit) (0 cr.)P: Cur­rent enrollment in graduate degree program in computer sci­ence. Provides for participation in graduate-level professional training and internship experience. 
• CSCI-Y 799 Computer Science Colloquium (1 cr.)A series of talks by researchers in computer science and closely related areas presenting their recent research. A minimum of 75% attendance and course work in the form of a written report based on the talk by any colloquium speaker are required for credit. 3
• CSCI-Y 890 Thesis Readings and Research (1-12 cr.)Research under the direction of a member of the graduate faculty leading to a Ph.D. dissertation.