103 courses with the subject CSC, each shown exactly as we captured it from the college's catalog, with every element we hold. Where the wording looks broken, that is our reading of the catalog, not the college's text.
Criminal Justice Elective ......................................................... - Total 15 Hampton University 2018-2020 Junior Year Semester 1st 2nd SOC 346 Statistics . ................................................................. 3 - Criminal Justice Elective ......................................................... 3 -
Logical basis of digital computer systems, algorithms, flow charts, programs, and program structure. Emphasis on computer knowl- edge using BASIC as a programming language. Application to con- temporary problems. Prerequisite: Permission of the Department Chair.
Natural Science Course. .......................................................... - Health (1) or Physical Education (2. ......................................... - Total 16 60 School of Business st 2nd Sophomore Year 3 Social Science Course ............................................................. 3 3 - HUM 201 Humanities I ............................................................ 3 - - 2 Free Elective. ............................................................................ - 2 - ECO 201 Macro Principles ....................................................... 3 - 3 ECO 202 Micro Principles ........................................................ - 3 - ACC 203 Accounting Principles I.............................................. 3 - 3 ACC 204 Accounting Principles II............................................. - 3 - MGT 215 Principles of Statistics. ............................................ 3 - 3 MGT 216 Quantitative Methods ............................................. - 3 14 Total 15 14 it Summer - Lower Division Internship (MBA 211) 1 Credit Junior Year Semester 1st 2nd 2nd MKT 305 Principles of Marketing ........................................... 3 - - MGT 301 Business Organization & MGT ............................... .3 - - MGT 305 Legal Environment of Business ............................... 3 - - MGT 323 Information/DP Systems ......................................... 3 - - MGT 340 Business Communication ........................................ 3 - - FIN 304 Business Finance. ....................................................... - 3 3 MGT 300 Business Research................................................... - 3 3 MGT 312 Personnel/HR Management. ................................... - 3 3 MGT 321 Management of International Business ................. - 3 3 MIS 302/ CIS 316 .................................................................... - 3 3 Total 15 15 15 Senior Year Semester 1st 2nd 2nd MGT 400 Organizational Behavior .......................................... 3 - - MGT 402 Production/Operations MGT ................................... 3 - - MIS 323/ CIS 310 .................................................................... 3 - 3 MIS 309/ CIS 320 .................................................................... 3 - 3 MIS 401/ CIS 323 .................................................................... 3 - 6 MGT 499 Business Policy & Strategy ..................................... - 3 - MIS 403/CIS 325 ..................................................................... - 3 MIS 406/CIS 410 ..................................................................... - 3 Free Elective. ............................................................................ - 3 120 Humanities Course................................................................... - 3 Total 15 15 TOTAL CREDITS FOR GRADUATION 120 Department of Business Administration The Department of Business Administration offers an integrated 5-year undergraduate/graduate program leading to two degrees upon completion: Bachelor of Science in Business Administration (B.S., at the end of 3.5 years) and Master of Business Administra- tion (MBA, at the end of 5 years). Department also offers a sepa- 2nd rate 2 year Master of Business Administration (MBA) program for - working professionals. - Five-Year Undergraduate and Graduate MBA - Program - The five-year MBA program includes 157 academic hours of course- 3 work with an imbedded undergraduate degree in Business Admin- - istration (Bachelor of Science). Competencies in the five-year MBA 3 are achieved through an interdisciplinary approach. This approach 3 includes liberal education curriculum; broad accounting, technology 2 and engineering-based business background; interpersonal skills; 14 and, structured and varied work experiences through internship. Hampton University 2018-2020
TOTAL 16
Problem solving techniques. Principles of good programming style, documen- tation, and robustness. Introduction to Data Structures. Object-Based and Object-Oriented Programming. Exception Handling. Files and Streams. Ethical Issues in Computing. Prerequisite: CSC 151.
in Computer Science Pjt. 3./Credit 1-3. Designed for freshman level undergraduates. Emphasis will be placed upon introduction to areas of computer science research, regular attendance at appropriate seminars, techniques of literature searches, and background study. This course may be taken twice. Prerequisite: Permission of the Depart- ment Chair.
Programming Lec. 3./Credit 3. Introduction to computer programming for business applications. Emphasis on algorithm development, structured program design, testing, implementa- tion, and documentation of business-oriented problems using COBOL as a language. Includes syntax, data and file structures, I/O media, and operating system facilities for implementing programs for report generation, data editing, table processing, and sequential file creation and access. Prerequi- site: CSC 152.
Computer structure. Machine language and instruction sets. Assembly coding. Addressing techniques. Binary arithmetic. Stor- age allocation. Subroutine linkage. Relocatability and program segmentation, bit manipulation. System I/O. Macros. Prerequisite: CSC 152. 280 Course Descriptions – Main Campus
and Organization I Lec. 3./Credit 3. Binary number representation and arithmetic. Computer structure. Addressing techniques. Storage allocation. Subroutine linkage. Relocatability and program segmentation, bit manipulation. Operating system supplied I/O routines and interface using a systems programming language and assembly language. Macros. Prerequisite: CSC 152 and MAT 117 or above.
and Organization II Lec. 3./Credit 3. Intermediate logic design including truth tables, logic diagrams, Boolean functions and Karnaugh maps. Computer architecture including CPU design, memory organization, I/O processing including programmed I/O, interrupt I/O, and direct memory access. Coding. Prerequisite: CSC 204.
Language Lec. 3./Credit 3. A study of C++ programming techniques and applications. Topics include arrays, functions, character strings, pointers, bit opera- tions, records, preprocessor, and file handling.
Lec. 3./Credit 3. Ada constructs for data types, branching, looping, arrays, subpro- grams, functions and procedures, recursion, fixed records, linked lists and tree structures. Basic concepts for packages, separate compilation, exceptions, and file I/O. Prerequisite: CSC 152.
Set theory, logic and combinatorics. Relations and functions. Proof techniques, including mathematical induction. Introduction to graph theory. Ethical princi- ples in computing. Prerequisite: CSC 152 and MAT 117 or above.
Topics include LISP data structures, built-in LISP functions including mapping functions. LISP programming techniques are illustrated with examples from artificial intelligence and symbolic manipulation application areas. Prerequi- site: CSC 152 and MAT 117 or above.
Study of FORTRAN language with emphasis on data representation. Control structures and iteration, block structures, subprograms, and debugging. Scientific and mathematical problem formulations. Corequisite: MAT 117 or above.
Algorithm Analysis I Lec. 3./Credit 3. Representation of compiler-defined data structures. Contiguous, linked, and hashed representations. Empirical and abstract analysis of time and space of competing representation. Space optimization. Specification, design, implemen- tation, and verification of linear and hierarchical; abstract data types, includin stacks, lists, queues, and trees. Basic techniques to algorithm design and analysis; ethical principles in computing. Prerequisite: CSC 152. Corequisite: CSC 215.
Algorithm Analysis II Lec. 3./Credit 3. An in-depth survey of data structures and algorithms, exploring their design, running efficiency, and applications. Advanced methods for internal and external sorting and searching. Implementation of relational data types including directed and undirected graphs. Advanced algorithms, which may include parsing, breadth-first and depth-first graph traversals, minimum weighted paths and information flow analysis; ethical principles in computing.
Sem./Pjt./Credit 1-6. Designed for sophomore level undergraduates. Emphasis will be placed upon introduction to basic techniques of conducting research and literature review, regular attendance at selected seminars, and directed work on a research project in computer sci- ence. This course may be taken twice. Prerequisite: Permission of the instructor.
Employment or training program in government or industry in which student makes significant use of computer science skills. ment Chair.
Introduction to file systems with an emphasis on file organization techniques. Multiprogramming and CPU scheduling. Memory management and virtual memory concepts. Deadlocks and recovery techniques. Process synchroni- zation and interprocess communication. Prerequisite: CSC 205 and CSC 251.
Lec. 3./Credit 3. Language definition structure. Data types and structures. Control structures and data flow. Run-time environments. Interpretive lan- guages. Lexical analysis and parsing.
Discrete, continuous, and hybrid simulation models. Random num- ber generation, distribution and transformation. Model validation. Problems illustrative of the models will be solved using simulation programming languages. Prerequisite: CSC 152 and MAT 305.
Lec. 3./Credit 3. Structured methodology of program design, development, testing, implementation, and documentation of typical business applica- tions. Includes file organization and access techniques, processing techniques, and the development of programs and systems of pro- grams for batch and interactive environments. Prerequisite: CSC 200 or comparable experience in COBOL programming. Hampton University 2018-2020
History and applications of microprocessors. Basic electronic prin- ciples. Logic elements, review of binary, octal, hexadecimal arith- metic. Study of the addressing modes and the instruction set for a specific chip. Machine language programming. Microprocessor hardware. Microcomputer architecture. Prerequisite: CSC 205.
Lec. 3./Credit 3. Introduction to database concepts. Hierarchical, network, and rela- tional models. Data normalization. Data description languages. Query facilities. File organization. Index organization. File security. Data integrity and reliability. Not for Computer Science or Com- puter Information Systems majors. Prerequisites: MAT 105 or 109 or above and CSC 120.
Treatment of types, attributes, tasks, concurrency of taskings, packages, encapsulation/data abstraction, dynamic allocation, generics, generic facilities, exception handling, program structure and separate compilation, representation clauses and implementa- tion features. Prerequisite: CSC 213.
Topics include basic communication concepts, data encoding and transmission methods, OSI layers and data link control protocols, multiplexing, common carrier services, networking and switching concepts. Not for Computer Science or Computer Information Sys- tems majors. Prerequisites: MAT 105 or 109 and CSC 120.
and Machine Learning Foundation Lec. 3./Credit 3. An introduction to the field of artificial intelligence. Problems, genres, techniques, and uses of artificial intelligence. Machine learning algorithms and tools for predictive modeling presented using case studies that inform their use in real-world applications. It will also address issues and concerns such as the ethics, bias, the effect artificial intelligence may have on society, and careers connected to artificial intelligence. Prerequisite: CSC 251.
Lec. 3./Credit 3. An introduction to the various technical and administrative aspects of Information Security and Assurance. This course provides the foundation for understanding the key issues associated with pro- tecting information assets, determining the levels of protection and response to security incidents, and designing a consistent, reasonable information security system, with appropriate intrusion detection and reporting features. The purpose of the course is to provide the student with an overview of the field of Information Security and Assurance. Students will be exposed to the spectrum of Security activities, methods, methodologies, and procedures. Coverage will include inspection and protection of information assets, detection of and reaction to threats to information assets, and examination of preand post-incident procedures, technical and managerial responses and an overview of the Information Security Planning and Staffing functions.
in Computer Science Sem./Pjt./Credit 1-9. Designed for junior level undergraduates. Emphasis will be placed upon conducting directed research in computer science with a des- ignated research mentor and regular attendance at selected semi- nars. Review basic literature search techniques. This course may be taken twice. Prerequisite: Permission of the instructor. Course Descriptions – Main Campus 281
A treatment of advanced topics of interest in Computer Science or Mathematics not routinely covered by existing courses. May be repeated when topics vary.
Concurrent processing. Problems of determinacy, deadlock, mutual exclu- sion, and synchronization. Resource allocation. Queuing and network control policies. Concepts of system balancing and thrashing. Protection. Advanced architecture and operating systems implementations. Introduction to telecommunications, networks, and distributed systems. Prerequisite: CSC 301.
Microprocessor, minicomputer, and mainframe architecture. Memory and storage organization, I/O organization, stack computers, parallel computers, overlap and pipeline processing systems, operating system architecture. Course Descriptions – Main Campus 287
Basic principles and techniques of computational complexity. Algo- rithms presented may include those from graph theory, pattern matching, polynomial and matrix arithmetic. Recurrence relations and dynamic programming. Emphasis on comparing algorithms.
Lec. 3./Credit 3. Introduction to software design paradigms, project management, system and software requirements, computer aided software engi- neering, and software design fundamentals using existing docu- mentation for a proposed system. In-depth survey of data flow- oriented, object-oriented, data-oriented, and real-time design. Team project involving the implementation of the proposed system using structured programming, information hiding, and strength and coupling measures. Software reviews. Software testing tech- niques and strategies. Software maintenance. Each student will be required to make an oral presentation as part of the team project.
and Development II Lec. 3./Credit 3. Team project involving the development of a project’s documentation from the Software Plan to a high-level design, using modern Software Engineering principles. CASE: tool use will be thoroughly integrated in documentation preparation. Various analysis methods, techniques, and formal methods will also be addressed. Each student will be required to make an oral presentation as part of the team project. Prerequisite: CSC 404.
Review of languages and their syntax and semantics. Concepts of parsing and ambiguity. Finite state grammars and recognizers. Lexical scanners. Imple- mentation of symbol tables. Theory and examples of context-free parsing techniques such as recursive descent, LL(k), precedence, LK(k), and SLR(k). Techniques of machine-independent code generation and improvement. Inherited and synthesized attributes. Syntax directed translation schema.
Axiomatic development of Boolean algebra and its application to switching circuits. Combinatorial circuits using logic connectives, different methods for the minimization of switching functions. Introduction to sequential machines, state diagrams, and flow tables. Prerequisites: CSC 301 and CSC 215.
Introduction to research problems in special areas of computer science.
Participation in research projects in collaboration with faculty supervisor, or original independent research problem. Prerequisite: Advanced Standing and Permission of the Department Chair.
Introduction to using microcomputers and major software packages such as spreadsheet, word processing, database management, graphics. Students will learn at least two different micro-computer systems. Prerequisite: CSC 120 or Permission of Instructor.
Topical discussion on current trends in computer science. Includes reports, guest lecturers, field trips, and technical writing skills.
and Formal Languages Lec. 3./Credit 3. Finite state concepts. Sequential machines and finite state transducers. State minimization. Formal grammar including Chomsky hierarchy grammars. Pushdown acceptors and linear bounded automata. Closure properties and algorithms of grammars. Computability and Turing Machines. Computable and non-computable functions. Prerequisite: CSC 308.
Survey of the field of artificial intelligence. Problem solving methods and searches through solution space. Predicate calculus for logic based systems. Expert systems. Knowledge representation. Machine learning. Computer vision.
Architectures of knowledge-based systems. Reasoning, knowledge, and control. Languages and tools for decision support systems. Prerequisite: CSC 430
Syntax, semantics and pragmatics of natural language. Parsers, and semantic interpreters. Classification and Vector spaces, probabilistic models, sequence models, attention models. Prerequisite: CSC 430
Fundamental concepts and methods of computational data analysis, including pattern classification, prediction, visualization, and recent topics in deep learning. Prerequisite: CSC 430
Fundamental issues in Big Data, Data Science, and Data Mining. Examine issues related to data organization, storage, retrieval, analysis and knowl- edge discovery at scale. Topics include large-scale data analysis, scalable computing frameworks, data storage systems, and semi-structured data models. Involves hands-on programming assignments and term project using real-world datasets. Prerequisite: CSC 430 and CSC 570
and Image Processing Lec. 3./Credit 3. A comprehensive introduction to computer vision. Major topics include image processing, detection and recognition, geometry-based and physics-based vision and video analysis. Students will learn basic concepts of computer vision as well as hands on experience to solve real-life vision problems.
Cognitive Robotics Lec. 3./Credit 3. Key elements of cognitive robotics, an emerging discipline that draws on robotics, artificial intelligence, and cognitive science. It will cover the essen- tials of traditional mobile and manipulator robotics and robot vision as well as the design of cognitive architectures to effect goal-directed action through perception, attention, planning, internal simulation, reasoning, and learning from demonstration. The course will emphasize both theory and practice and it will make use of physical mobile robots and manipulator arms, as well as robot simulators. Prerequisite: CSC 433
Biometrics is capturing and using physiological or behavioral characteris- tics for personal identification. It is set to become the successor to the PIN. This course will introduce computational methods for the implementation of various biometric technologies including face and voice recognition, finger- print and iris identification, and DNA matching. Prerequisite: CSC 434
Artificial Intelligence Lec. 3./Credit 3. A treatment of advanced topics of interest in Artificial Intelligence not routinely covered by existing courses. May be repeated when topics vary. Prerequisite: r CSC 430
Network Security Lec. 3./Credit 3. Introduction to security problems in computing and networking. Information Security Models. Encryption and decryption techniques. Cryptographic protocols and practices. Operations Security. Program Security. Security in networks and distributed systems. Database Security. Electronic commerce security. Legal and ethical issues in computer and network security. Prerequisite: CSC 382. Hampton University 2018-2020
Management, and Certification Lec. 3./Credit 3. Outlines the principles of systems security administration, management, and certification. Provisioning, procurement and installation of network, hardware and software systems for mission critical enterprises. System configuration and maintenance. Incident handling and response. Facilities Management. Contingency Plans. Law, standards of contract. Operations Management. System certification, testing and validation. Prerequisite: CSC 382.
Outlines the aspects of computer security and risk management. Accreditation, implementation, extension, and operation principles for secure information systems. Security policy and plan develop- ment. Contingency, continuity and disaster recovery planning. Inci- dent handling and response. Prerequisite: CSC 382.
for Senior Management Lec. 3./Credit 3. Develops the knowledge necessary for senior security management to analyze and judge the reported systems for validity and reliability to ensure such systems will operate at a proposed trust level. Topical review and discus- sion on current trends in cybersecurity standard. Includes grant final approval to operate, grant review accreditation, verify compliance, ensure establish- ment of security controls, ensure program managers define security in acquisitions, assign responsibilities, define criticality and sensitivity, allocat resources, multiple and joint accreditation, assess network security. Prereq- uisite: CSC 382.
in Computer Science Sem./Pjt./Credit 1-12. Designed for senior level undergraduates. Emphasis will be placed upon participating in an independent research project or making a major contri- bution to departmental research with a designated research mentor. The student will produce a publication quality research report or thesis. Regular attendance at the computer science seminar series is also required. This course may be taken twice. Prerequisite: Permission of the Department Chair. CSC (Computer Science –
Problem solving using a high-level language. Problem analysis, top-down design and stepwise refinement. Programming language concepts of input/ output, data representation, data types, iteration, recursion, subroutines, and parameter passing. Aspects of syntax and semantics of a high level program- ming language.
Data structuring mechanisms. Recursive functions and procedures. Abstract data types. Traversal algorithms. Principles of good programming style. Introduction to sorting, searching and algorithm analysis. Prerequisite: CSC 501 or Permission of the Department Chair.
Binary number representations. Computer structure. Addressing techniques. Storage allocation. Subroutine linkage. Relocatability and program segmentation. Systems programming at various levels. Macros.
Lec. 4./Credit 4. Review of structured programming. Definitions and implementa- tion of data structures, such as stacks, queues, lists, trees, graphs, strings, and files. Data abstraction, algorithms, recursion, and iteration. Relations among data structures, algorithm structures, and analysis of algorithms. Prerequisite: CSC 502 or Permission of the Department Chair.
and Operating Systems Lec. 4./Credit 4. Principles of computer design, processor and storage organization, I/O organization. Microcomputer, minicomputer, and mainframe architec- tures. Assembly languages and functions of operating systems, such as I/O functions, file management, resource allocation. Deadlocks and recovery techniques. Multiprogramming, multiprocessing, and distributed systems.
Chomsky hierarchy and programming languages. Language definitions. Data types and structures. Control structures and data flow. Syntax, semantics, design, and implementation of programming languages. Lexical analysis, parsing and code generation.
Propositional and Predicate Calculus. Proof techniques. Queuing theory. Mathematical formulations of data structures. Basic models of computation expressions and grammars. Prerequisite: CSC 215 and CSC 252.
Automata theory, models of computation, computability, introduc- tion to complexity theory. Prerequisite: CSC 510.
Basic graphics programming and graphics packages. Graphics hardware. Transformations, 3D graphics, modeling, shading, intensity, hidden elements, color. Prerequisite: CSC 205, CSC 252 and MAT 152.
Lec. 3./Credit 3. A treatment of topics in mathematical foundations not routinely covered by other courses. Prerequisite: CSC 510 or Permission of the instructor.
Lec. 3./Credit 3. A treatment of topics in not routinely covered by other courses.
A treatment of topics in not routinely covered by other courses. Course Descriptions – Main Campus 283
An overview of object oriented programming foundations and styles: reusability and object oriented analysis, design, and coding. Detailed inves- tigation of object oriented programming concepts such as objects, classes, inheritance, messages, encapsulation.
Introduces various software and hardware systems useful for research in Computer Science. Particular emphasis is placed on tools found in the UNIX and DOS environment on platforms such as workstations, PC’s and parallel machines.
A treatment of topics not routinely covered by other courses.
Lec. 3./Credit 3. A treatment of topics in not routinely covered by other courses.
Syntax and semantics of high level languages. Lexical analysis, parsing, code generation, and optimization.
A treatment of topics not routinely covered by other courses.
Lec. 3./Credit 3. Introduction to database concepts. Hierarchical, network, and rela- tional models. Data normalization. Data description languages. Query facilities. File organization. Index organization. File security. Data integrity and reliability.
Networks Lec. 3./Credits 3. Data communication concepts involving signaling, modulation, transmission methods, interfaces, multiplexing, data integrity and security. Principles of communication architectures and networks. Standard communication archi- tectures. Switching and routing concepts. Classification and fundamental operations of networks. Network design principles. Medium access protocols. Internetworking and advanced data transmission concepts. Prerequisite: CSC 205.
A treatment of topics not routinely covered by other courses. Pre- CSC (Computer Science – Graduate Only)
Numerical and optimization methods useful for simulation, graph- ics, and image processing. Computation statistics and Monte Carlo methods. Signal analysis foundations. Prerequisite CSC 510 or Per- mission of the instructor. 284 Course Descriptions – Main Campus
Relation between architectures and operating systems. Multiprogram- ming, time-sharing, multiprocessing, distributed processing, and real time processing. Interprocess communication and synchronization. Resource allocation and related problems.
Data transport characteristics and topologies; the frame formats and proto- cols for messages; the physical, data link, network and transport layers; network performance evaluation. Prerequisite: CSC 620 or Permission of the instructor.
Parallel processing models and architectures. Concurrent processes and controls. Parallel algorithms and their analysis. Prerequisite: CSC 620 or Permission of the instructor.
Principles of computer design. Architectures of sequential and parallel computers. Prerequisite: CSC 620 or Permission of the instructor.
A treatment of topics not routinely covered by other courses. Pre-
Problem solving techniques and search. Knowledge representation schemes such as frames, rules, and predicate calculus. Machine learning. Application areas such as natural language processing, expert systems, and computer vision.
Architectures of knowledge-based systems. Reasoning, knowledge, and control. Languages and tools for decision support systems. Prerequisite: CSC 630 or Permission of the instructor.
Syntax, semantics and pragmatics of natural language. Parsers, and semantic interpreters. Prerequisite: CSC 630 or Permission of the instructor.
Lec. 3./Credit 3. A treatment of topics not routinely covered by other courses.
Foundations Lec. 3./Credit 3. Software engineering paradigms. Formal specification, design, verification and maintenance.
A survey a software analysis and testing techniques. Six program views (textual, syntactic, control flow, data flow, computation flow, and functional) and analysis techniques based on those view. A taxonomy of testing techniques including specification-oriented, implementation-oriented, and error-oriented, and hybrid methods. Evaluation of testing techniques and test cases. Prerequisite: CSC 640 or Permission of the instructor. Hampton University 2018-2020
A treatment of topics not routinely covered by other courses.
Chomsky hierarchy. Turing machines, decidability and computational complexity.
Turing machines and equivalent computational models. Church’s thesis. Complexity classes. Prerequisite: CSC 510, CSC 650 or Permission of the instructor.
Lec. 3./Credit 3. A treatment of topics not routinely covered by other courses. Pre-
Chomsky Hierarchy and programming languages. Language definitions, data types, and structures. Control structures and data flow. Syntax, semantics, design and implementation of programming languages. Lexical analysis and parsing.
Lec. 3./Credit 3. A treatment of topics not routinely covered by other courses.
Research on problems leading to a thesis.
Students will engage in co-teaching a low-level computer science course.
Research on problems leading to a thesis.
This course documents preparation for the written Master’s thesis.
This course documents completion of the written Master’s thesis and oral defense of that thesis.
Graded S/U only.
This credit will not count towards the degree. Graded S/U only.
Source: Hampton University's catalog, linked per course · table learning_unit · CourseShelf publish 59
