CMPT183: Foundations of Computer Science I (2 hours lecture, 2 hours lab)

Basic theory of digital computers. Syntax and semantics of a programming language. Algorithms: logic, design, testing and documentation. 3 sh.

Prerequisites: MATH 100, MATH 112, MATH 114, MATH 116, MATH 122 or MATH 221.

CMPT184: Foundations of Computer Science II (3 hours lecture)

Continuation of CMPT 183. Algorithm development involving user functions; subroutines, recursions, structures file manipulation. 3 sh.

Prerequisites: CMPT 183.

CMPT280: Assembly Language and Computer Architecture (3 hours lecture)

Computer structures, the conventional machine level, introduction to assembler language. 3 sh.

Prerequisites: CMPT 184.

CMPT281: Theory of Digital Machines (3 hours lecture)

Microprogramming level of a computer, the operating system level, gates, sequential and combinational circuits, flip-flops, registers, number codes. 3 sh.

Prerequisites: CMPT 280 and CMPT 285.

CMPT285: Discrete Mathematical Structures (3 hours lecture)

The structures include sets, graphs, digraphs, trees, networks, lattices, matrices, semigroups and groups. Many practical business and scientific problems can be posed and solved by the use of these structures. 3 sh.

Prerequisites: MATH 112.

CMPT287: Data Structures, File Structures and Algorithms (4 hours lecture)

Creation and manipulation of in-memory data structures including graphs, lists, queues, sets, stacks and trees; searching, sorting and other algorithms for in-memory data structures. File, file structures and external sorting. Meets the University Writing Requirement for majors in Computer Science and Science Informatics. 4 sh.

Prerequisites: CMPT 184. Prerequisite or co-requisite: CMPT 285.

CMPT363: Introduction to Numerical Computing (3 hours lecture)

Fundamentals of numerical computation, with emphasis on basic algorithms and their efficient implementation: appropriate treatment of theoretical bases. Topics include floating point arithmetic, roundoff error and propagation, numerical solution of nonlinear equations, interpolation and approximation, and numerical integration. The Fortran language will be taught and used in programming assignments. 3 sh.

Prerequisites: CMPT 183 and MATH 221.

CMPT371: Software Engineering I: Analysis and Design (4 hours lecture)

Utilization of software engineering principles and techniques for the specification, analysis, and design of high-quality complex software systems including both technical and non-technical aspects. 4 sh.

Prerequisites: CMPT 287.

CMPT372: Software Engineering II: Implementation and Testing (4 hours lecture)

This course utilizes software engineering principles and techniques for the implementation, testing and maintenance of high-quality complex software systems, as designed in a previous course (CMPT 371). 4 sh.

Prerequisites: CMPT 371.

CMPT385: Computer System Organization (3 hours lecture)

Introduction to chip technology, microprocessors, microcomputers, architecture, instruction sets and programming of microcomputers, and other bus-oriented computers. 3 sh.

Prerequisites: CMPT 281.

CMPT387: Principles of Data Communications (3 hours lecture)

Fundamentals of data communication topics. Analog Digital, Broadband-Baseband, TDM-FDM, AM-FM techniques. Error codes and protocols. 3 sh.

Prerequisites: CMPT 281.

CMPT388: Foundations of Artificial Intelligence (3 hours lecture)

A general, comprehensive coverage of the main areas constituting the field of artificial intelligence, introduction of computer vision, natural language processing (NLP), pattern recognition and neural networks. 3 sh.

Prerequisites: CMPT 371.

CMPT472: Computer Graphics (3 hours lecture)

An introduction to computer graphics, including the algorithms to generate two-dimensional and three-dimensional graphical pictures. An overview of interactive graphics and graphics devices. 3 sh.

Prerequisites: CMPT 287 and MATH 335.

CMPT481: Operating Systems (3 hours lecture)

Process Management. Process synchronization and deadlock prevention. Memory Management. Interrupts processing. I/O Control. 3 sh.

Prerequisites: CMPT 371.

CMPT483: Database Systems (3 hours lecture)

A comprehensive collection of database organizations and design tools: file organizations and evaluations, database structures, schemata and implementations. Database security, operations and management. 3 sh.

Prerequisites: CMPT 371.

CMPT484: Fundamentals of Programming Languages (3 hours lecture)

Syntax and semantics of modern programming languages with emphasis on programming in the large, functional, logic, and object-oriented paradigms. Common threads found in both imperative and non-imperative languages discussed. 3 sh.

Prerequisites: CMPT 371.

CMPT485: Compiler Construction (3 hours lecture)

Introduction to the concepts and techniques used in the description of programming languages and in the construction of compilers. 3 sh.

Prerequisites: CMPT 484.

CMPT486: Design of Computer Interfaces (3 hours lecture)

Basic digital and analog computing circuits and interface circuits, computer-telecommunication interfaces. 3 sh.

Prerequisites: CMPT 385.

CMPT487: Local Area Networks (LAN's) (3 hours lecture)

Overview, topology, taxonomy, transmission, technology media and control protocols of microcomputer LAN's. 3 sh.

Prerequisites: CMPT 387.

CMPT493: Advanced Database Theory (3 hours lecture)

This course continues the introduction to data management. Topics include: security, integrity, concurrency and recovery, query optimization, file structures and other performance issues. 3 sh.

Prerequisites: CMPT 483.

CMPT495: Topics in Computer Science for Undergraduates

Study of specialized topics in computer science. May be repeated once for a maximum of 6.0 credits as long as the topic is different. 1 - 3 sh.

Prerequisites: CMPT 287 and departmental approval.

CMPT497: Undergraduate Research in Computer Science I

Individual research in areas of computer science agreed upon by the student and the instructor. The results of the research will be a basis of a seminar or colloquium to be given by the student. Students must not accumulate more than 6 credits total in courses CMPT 497, 498, MATH 497, 498. 1 - 3 sh.

Prerequisites: CMPT 281, MATH 335, and departmental approval.

CMPT498: Undergraduate Research in Computer Science II

Individual research in areas of computer science agreed upon by the student and the instructor. The results of the research will be a basis of a seminar or colloquium to be given by the student. Students must not accumulate more than 6 credits total in courses CMPT 497, 498 MATH 497, 498. 1 - 3 sh.

Prerequisites: CMPT 281, MATH 335, and departmental approval.

CMPT499: Cooperative Education in Computer Science

The study of theoretical ideas of computer science combined with their practical applications in a real life environment. The co-op experience is a semester working off-campus under the guidance of a company supervisor, and a faculty supervisor. Only 3 of the 8 credits may be used to fulfill the major requirement. 3 - 8 sh.

Prerequisites: CMPT 320 or CMPT 371 and departmental approval.

ECON101: Principles of Economics: Macro (3 hours lecture)

A study of the American economy, analytically and institutionally; the achievement of an optimal allocation of resources, price stability, full employment level of national income and long term growth. Meets Gen Ed 2002 - Social Science, Social Science. 3 sh.

ECON102: Principles of Economics: Micro (3 hours lecture)

Organization and operation of the American economy for the production and distribution of goods and services. Pricing of products and factors of production in market situations varying from competition to monopoly. Resource allocation, price determination and behavior of the firm in the determination of quantity of output and the hiring of factors of production. Meets Gen Ed 2002 - Social Science, Social Science. 3 sh.

MATH122: Calculus I (4 hours lecture)

Limits, continuity; derivative and differentiation; applications of the derivative, maxima, minima, and extreme considerations; antiderivatives; Riemann integral. 4 sh.

Prerequisites: MATH 111 or MATH 112 or placement through the Montclair State University Placement Test (MSUPT) or a satisfactory score on department's Calculus Readiness Test. (Students who did not satisfy the course prerequisite at MSU and students who received a grade of D-, D, or D+ in the prerequisite course taken at MSU are required to demonstrate competency on the department's Calculus Readiness Test.)

MATH221: Calculus II (4 hours lecture)

Riemann integral applications, transcendental functions, techniques of integration, improper integrals, L'Hospital's rule, infinite series. 4 sh.

Prerequisites: MATH 122.

MATH335: Linear Algebra (4 hours lecture)

The course content will cover the foundations of the algebra of vector spaces, matrix operations, matrix invertibility theorems, linear independence, span, basis, linear transformations, finite dimensional Hilbert Spaces, Gram-Schmidt process, projections, eigenvalues and eigenvectors, and applications. The focus of the course will be to develop advanced mathematical skills in reading and understanding abstract mathematical definitions, constructing examples, and developing mathematical proofs. Meets the University Writing Requirement for majors in Mathematics. 4 sh.

Prerequisites: MATH 222 or equivalent.

MGMT231: Management Processes (3 hours lecture)

To provide undergraduate students a review of classical and modern approaches to the managerial process as it relates to the manager's functions of planning, organizing, communication, motivation, leading, controlling, and managing change. Emphasizing new forces in the managerial environment such as workplace diversity and economic globalization, these reviews will be tied to the open-system model and the contingency approach as overall frameworks for understanding organizations and management. 3 sh.

Prerequisites: ENWR 105 or HONP 100.

STAT330: Fundamentals of Modern Statistics I (3 hours lecture)

Displaying, describing and modeling data; arrangements for producting data; probability; methods for drawing conclusions from data: significance testing, confidence interval estimation, linear regression, analysis of variance. Examples from many disciplines including the social and natural sciences. Statistical software is used. 3 sh.

Prerequisites: MATH 221.