• Two courses (6 credits) of M.S. Category A, with a grade of B or better
  • Two courses (6 credits) of M.S. Category B, with a grade of B or better
  • Two courses (6 credits) from either category A or category B
  • Four courses (12 credits) from the list of courses acceptable for CS graduate credit, including courses from M.S. Categories A and B, acceptable undergrad courses, approved courses in other departments, CS seminars, and independent study. However, at most one of the four courses may be an independent study.

A culminating sequence (6 credits) consisting of:

  • Two additional courses from the union of M.S. Categories A and B, plus an M.S. essay approved according to the requirements of the School of Graduate Studies.
  • 6 credits of M.S. Thesis research 704, 705, 706 plus an M.S. thesis defended successfully according to the requirements of the School of Graduate Studies.
  • 6 credits of 601, 602 and successful completion of the Ph.D qualifying exam in Computer Science. (In this case, the Ph.D. qualifying paper will satisfy the writing requirement of the School of Graduate Studies).

M.S. Category A

M.S. Category B

Approved M.S. Classes from Other Departments

125 Biomedical Engineering

520 Neuroelectric Systems
526 Brain Dynamics
610 Advanced Topics in Computers in Biomedical Engineering
620 Neural Networks and Neurocomputing

185 Cognitive Sciences

500 Proseminar in Cognitive Science

540 Industrial and Systems Engineering

515 Stochastic Models in Industrial Engineering
525 Applied Queuing Theory
540 Computational Methods for Industrial Engineering
575 Advanced Engineering Economics I
585 System Reliability Engineering I
685 System Reliability Engineering II

625 Linguistics

510 Syntax I
511 Syntax II
514
520 Phonology I
521 Phonology II
524
530 Semantics I
531 Semantics II
534

640 Mathematics

551 Abstract Algebra I,II
561 Mathematical Logic
566 Axiomatic Set Theory
567 Model Theory
569 Selected Topics in Logic

642 Applied Mathematics

516 Applied Partial Differential Equations
527 Methods of Applied Mathematics
528 Methods of Applied Mathematics
550 Linear Algebra and Applications
551 Applied Algebra
575 Numerical Solutions of Partial Differential Equations
577 Selected Mathematical Topics in System Theory
578 Selected Mathematical Topics in System Theory
581 Graph Theory
582 Combinatorics
583 Combinatorics
587 Selected Topics in Discrete Mathematics
588 Introduction to Mathematical Techniques in Operations Research
589 Topics in Mathematical Techniques in Operations Research
591 Topics in Probability and Ergodic Theory
592 Topics in Probability and Ergodic Theory
611 Selected Topics in Applied Mathematics

711 Operations Research (RU Newark)

513 Discrete Optimization
553 Boolean and Pseudo-Boolean Functions
556 Queuing Theory
558 Convex Analysis and Optimization

730 Philosophy

513 Logic and Natural Language
550 Seminar in Epistemology
570 Seminar in Philosophy of Language
575 Seminar in Philosophy of Mind
650 Advanced Topics in Epistemology
670 Advanced Topics in Philosophy of Language
675 Advanced Topics in Philosophy of Mind
676 Advanced Topics in Philosophy of Psychology
678 Advanced Topics in Decision Theory
679 Topics in Logic

830 Psychology

514 Sensation and Perception
515 Computational Vision
535 Language and Communication
540 Mathematical Models of Learning, Perception, Cognition
546 Memory and Attention
547 Computational Models of Cognition
550 Language Development
602 Psycholinguistics
611 Seminar: Perception
635 Seminar: Selected Topics in Learning
637 Seminar: Cognition
641 Seminar: Thinking

954 Statistics-Data Science

581 Probability and Statistical Theory for Data Science (REQUIRED)
553, 554, 555, 563, 565, 576, 580, 582, 583, 586, 587, 588, 590, 591, 592, 593, 595
596 Regression and Time Series Analysis for Data Science
652, 653, 654, 681, 682, 690, 697, 668

960 Statistics

553 Categorical Data Analysis
554 Applied Stochastic Processes
555 Nonparametric Statistics
563 Regression Analysis
576 Survey Sampling
580 Basic Probability
581
582 Introduction to Methods and Theory of Probability
583 Methods of Inference
586 Interpretation of Data I
587 Interpretation of Data II
588 Data Mining
590 Design of Experiments
591 Advanced Design of Experiments
592 Theory of Probability
593 Theory of Statistics
595 Intermediate Probability
596 Intermediate Statistical Methods
652 Advanced Theory of Statistics I
653 Advanced Theory of Statistics II
654 Stochastic Processes
681 Advanced Probability Theory II
682 Individual Studies in Statistics
690 Special Topics
697
668 Bayesian Data Analysis

960 Statistics (MBA)

641 Analytics for Business Intelligence

Electrical and Computer Engineering

505 CONTROL SYSTEM THEORY
506 APPLIED CONTROLS
526 ROBOTIC SYSTEMS ENGINEERING
527 DIGITAL SPEECH PROCESSING
529 IMAGE CODING AND PROCESSING
539 ADVANCED TOPICS IN DIGITAL SIGNAL PROCESSING: INTRODUCTION TO FUNCTIONAL NEUROIMAGING, METHODS AND DATA ANALYSIS
542 INFORMATION THEORY AND CODING
543 COMMUNICATION NETWORKS I
544 COMMUNICATION NETWORKS II
553 WIRELESS ACCESS TO INFORMATION NETWORKS
560 COMPUTER GRAPHICS
561 MACHINE VISION
562 VISUALIZATION AND ADVANCED COMPUTER GRAPHICS
563 COMPUTER ARCHITECTURE I
564 COMPUTER ARCHITECTURE II
565 NEUROCOMPUTER SYSTEM DESIGN
566 INTRODUCTION TO PARALLEL AND DISTRIBUTED COMPUTING

567 SOFTWARE ENGINEERING I
568 SOFTWARE ENGINEERING WEB APPLICATIONS
570 ROBUST COMPUTER VISION
571 VIRTUAL REALITY TECHNOLOGY
574 COMPUTER-AIDED DIGITAL VLSI DESIGN
575 VLSI ARRAY PROCESSORS
576 TESTING OF ULTRA LARGE SCALE CIRCUITS
578 DEEP SUBMICRON VLSI DESIGN
579 ADVANCED TOPICS IN COMPUTER ENGINEERING
588 INTEGRATED TRANSISTOR CIRCUIT DESIGN