Department Chair: Ling Zheng
Graduate Program Director: Jay Wang
The Master of Science in Computer Science provides a broad background in graduate-level computer science study. The thirty- to forty two-credit program allows the student to choose a thesis option or a non-thesis option. Students may also choose to specialize in Cybersecurity, Databases and Intelligent Information Systems, or Computer Networks. When the applicant has a strong background in computer science, such as a bachelor’s degree in computer science with excellent standing, up to twelve credits (CS-501B Program Development (3 cr.)-CS-505 Operating Systems Concepts (3 cr.)) may be waived. Other majors may be required to take some or all of these courses. These foundation courses must be completed with a minimum GPA of 3.0, and all prerequisite courses must be passed with a grade of “B-” or better.
The Master of Science in Data Science offers a compelling pathway for students with or without a strong background in computer science to develop the skills needed to enter the highly attractive job market for data scientists and data analysts. The program emphasizes project-based learning, providing students with hands-on experience working with real-world data from a variety of disciplines. Students will engage in projects in collaboration with external partners, addressing questions that can be solved using a range of data science techniques. Graduates of the program will be well positioned to compete in the job market across a variety of fields, having gained broad experience in data analysis methods as well as skills in data visualization and in communicating results effectively in both written and oral forms.
Weihao Qu, Assistant Professor (Graduate Faculty). B.S., Tianjin University; M.S., University at Buffalo; Ph.D., Boston University. Programming language research including semantics, type systems, proof systems and program analysis, artificial intelligence, security and deep learning, formal verification, penetration testing, and differential privacy.
wqu@monmouth.edu
Richard Scherl, Associate Professor (Graduate Faculty). B.A., Columbia University; M.A., University of Chicago; Ph.D., University of Illinois. Interests include artificial intelligence (especially knowledge representation, automated reasoning and natural language processing), cognitive science, and databases.
rscherl@monmouth.edu
Jiacun Wang, Professor and Graduate Program Director (Graduate Faculty). B.S., Jiangsu University of Science and Technology; Ph.D., Nanjing University of Science and Technology, China. Interests include software architecture, Petri nets, real-time systems, discrete event systems, telecommunications, and networking.
jwang@monmouth.edu
Cui Yu, Associate Professor (Graduate Faculty). B.S., Nanjing University of Aeronautics and Astronautics; Ph.D., University of Singapore, Singapore. Interests include database management systems, spatial databases, and information storage and retrieval.
cyu@monmouth.edu
Ling Zheng, Associate Professor and Chair (Graduate Faculty). B.S., Southern Medical University, Guangzhou, China; M.S., Zhejiang University, Hangzhou, China; Ph.D., New Jersey Institute of Technology. Healthcare information systems, translational bioinformatics, biomedical ontologies/terminologies, and biomedical knowledge representation and discovery.
lzheng@monmouth.edu
CS-501A Computer Programming EssentialsCredits: 3
Term Offered: All Terms
Course Type(s): TPS
An introduction in computer programming for newly admitted graduate students. Students will learn basic concepts in modern computer programming. Students will complete all the programming exercises and assignments in the modern objected-oriented language.
CS-501B Program DevelopmentCredits: 3
Prerequisite(s): CS-501A passed with a grade of B- or higher
Term Offered: All Terms
Course Type(s): None
Continuation at the coverage of the same modern object-oriented language introduced in CS-501A. More advanced object-oriented design, including inheritance and polymorphism.
CS-502 Theoretical Foundations of Computer ScienceCredits: 3
Term Offered: All Terms
Course Type(s): None
Concepts, methods, models, and associated computer exercises for important topics in discrete mathematics and probability. Includes: logic and mathematical reasoning, functions, sets, summations, asymptotic notation, algorithms and complexity, number theory, cryptography, matrix algebra, induction and recursion, counting techniques, combinatorial objects, discrete structures, discrete probability theory, relations, graph theory, moments, random variables, and graph algorithms. Limited to Computer Science majors.
CS-503 Data Structures and AlgorithmsCredits: 3
Prerequisite(s): CS-501B passed with a grade of B- or higher
Term Offered: All Terms
Course Type(s): None
Design and implementation of fundamental data structures and algorithms, including: linked lists, hashing, sorting, trees, stacks, queues, sets and bags, and recursion. Application to problem solving and object-oriented design of moderate-sized programs.
CS-505 Operating Systems ConceptsCredits: 3
Prerequisite(s): CS-503 passed with a grade of B- or higher
Term Offered: All Terms
Course Type(s): None
The basic concepts of operating systems from the point of view of an advanced user: the interaction of the kernel, the command interpreter, and user processes. Focus is on process and resource management, concurrency control, and inter-process communication. Examples and projects are based mainly on Unix. The course also includes an introduction to computer architecture from an operating-systems perspective (processors, devices, interrupts, clocks, etc.).
CS-509 Advanced Object-Oriented Programming and DesignCredits: 3
Prerequisite(s): CS-501B passed with a grade of B- or higher
Term Offered: Spring Term
Course Type(s): None
Object-oriented programming and design, using a language different from that used in CS 501B. Used in classes, inheritance, polymorphism, and libraries.
CS-512 Algorithm DesignCredits: 3
Prerequisite(s): CS-502 and CS-503 both passed with a grade of B- or higher
Term Offered: Spring Term
Course Type(s): CISEL
Design and analysis of algorithms; dependence of algorithm efficiency on data structure choice; correctness of algorithm implementation and basic design techniques and their applications to programming with fundamental data structures.
CS-514 NetworksCredits: 3
Prerequisite(s): CS-501A
Term Offered: All Terms
Course Type(s): CISEL
An introductory-level course on the hierarchy of networking software and hardware. Particular emphasis on Medium Access Control, Network layer, Transport layer, and Session layer. Several MAC-layer protocols, TCP/IP. Also listed as MIS-514. Prerequisite: CS-501A
CS-517 Database Design and ManagementCredits: 3
Prerequisite(s): CS-503 passed with a grade of B or higher
Term Offered: All Terms
Course Type(s): CISEL
Introduction to database systems, data modeling, design theory and methodologies, query languages and query processing. Coverage of relational database model and design, normalization process, SQL, hands-on database design and application development. Also listed as MIS-517.
CS-518 Fundamentals of Computer Security and CryptographyCredits: 3
Prerequisite(s): CS-514 passed with a grade of B- or higher.
Term Offered: Fall Term
Course Type(s): CISEL
An introduction to computer security and its related issues, including cryptography. It covers threats assessment, security policies, basic cryptography, security mechanisms, and assurance. Also includes several case studies on enhancing the security level of specific systems by integrating different security mechanisms and techniques. Both theoretical and practical issues are addressed in the course. Students who successfully complete this course will be capable of assessing the threats, enhancing the security, and evaluating the assurance level of specific computer systems.
CS-520 Introduction to Artificial IntelligenceCredits: 3
Prerequisite(s): CS-502 and CS-503.
Term Offered: All Terms
Course Type(s): CISEL
Introduction to methods and algorithms used to incorporate intelligence into computer programs. Topics include search techniques, representation and reasoning, and machine learning. Applications of these methods are stressed. Also covers implementation of some of the fundamental algorithms.
CS-521 Databases for AI and Machine LearningCredits: 3
Prerequisite(s): CS-503 and CS-517 both passed with a grade of B- or higher.
Term Offered: Spring Term
Course Type(s): None
This course introduces modern database technologies that underpin contemporary AI and Machine Learning systems. Emphasis is placed on data warehouses, data lakes, vector databases, time-series databases, graph databases and feature stores. Students will gain theoretical foundations and hands-on experience designing, implementing, and evaluating data architectures for large-scale ML training and real-time inference systems.
CS-522 Data Integration, Information Extraction, and Knowledge CreationCredits: 3
Prerequisite(s): CS-503.
Course Type(s): CISEL
Coverage of the fundamental techniques for integrating information from heterogeneous sources to obtain actionable knowledge. The sources of information include databases, files, and Web pages. Covered techniques include both those based upon logic and also approaches based on probabilistic reasoning.
CS-525 SimulationCredits: 3
Prerequisite(s): CS-502, CS-503, and CS-514 all passed with a grade of B- or higher
Term Offered: Spring Term
Course Type(s): None
Formal models of discrete event systems, computer simulation of models, and analysis of simulation results. Discrete event simulation is applied to studying the performance of computer and communication systems. Object-oriented design and programming in C++.
CS-529 Web Services and .NETCredits: 3
Prerequisite(s): CS-503 passed with a grade of B- or higher
Term Offered: Spring Term
Course Type(s): CISEL
Introduction to Web services. Theoretical and practical coverage of client-server architecture, communication protocols, and messaging, including XML and SOAP transactions. .NET Framework architecture is used for the applications. We contrast with other platforms, e.g., Java-based Web services. Students implement Web services and simple clients on PCs or mobile devices.
CS-532 Compiler DesignCredits: 3
Prerequisite(s): CS-512 passed with a grade of B- or higher
Term Offered: Spring Term
Course Type(s): CISEL
The major techniques used in compiler writing, lexical analysis, syntax analysis, storage management, error detection and recovery, and code generation. Tools for compiler writing (LEX, YACC, etc.).
CS-533 Database System ImplementationCredits: 3
Prerequisite(s): CS-502 and CS-503 both passed with a grade of B- or higher
Term Offered: Fall Term
Course Type(s): CISEL
DBMS architecture, data storage and indexing, query processing and optimization, transaction management and recovery, and some issues related to advanced database applications.
CS-535 TelecommunicationsCredits: 3
Prerequisite(s): CS-502, CS-505, and CS-514 all passed with a grade of B- or higher
Term Offered: Fall Term
Course Type(s): None
In-depth coverage of the lower layers of the network hierarchy: Physical layer, Data Link layer, Network layer, and Transport layer.
CS-550 Computer System ArchitectureCredits: 3
Prerequisite(s): CS-502 and CS-503 both passed with a grade of B- or higher
Term Offered: Spring Term
Course Type(s): None
Computer system interconnection structures, central processing unit, control unit, microprogrammed control, memory organization, cache and virtual memory, computer arithmetic, RISC processors, introduction to parallel processing, and case studies.
CS-588 Computer Science Practice and ExperiencesCredits: 1
Prerequisite(s): 18 credits in Computer Science or Software Engineering
Term Offered: All Terms
Course Type(s): None
Provides opportunity for Computer Science graduate students to obtain related experience in employment at a local company or institution with Monmouth University sponsorship. Available to Computer Science graduate students who have completed at least eighteen credit hours of graduate courses (500 level), with a minimum GPA of 3.00. Does not satisfy elective requirements. Students may take the course a maximum of two times. This is a pass/fail course. Departmental approval is required to take this course.
CS-598 Special Topics in Computer ScienceCredits: 3
Term Offered: All Terms
Course Type(s): CISEL
Subject matter varies with the interest of the students and of the professor teaching the course. The exact nature of the topic covered in any given semester is indicated in the student's transcript.
CS-599 Independent Study in Computer ScienceCredits: 3
Term Offered: All Terms
Course Type(s): None
Independent study in a topic not substantially treated in a regular graduate course, for students with superior ability; weekly consultation. Prior permission of directing professor and the graduate program director is required to take this course. This course can only be taken once for credit. Completion of all foundation and core courses and a minimum G.P.A. of 3.50 is required to take this course.
CS-611 Secure Web Services DesignCredits: 3
Prerequisite(s): CS-501B passed with a grade of B- or higher
Term Offered: Spring Term
Course Type(s): CISEL
Web applications present a complex set of security issues for architects, designers, and developers. The most secure and hack-resilient Web applications are those that have been built from the ground up with security in mind. This course focuses on principles of secure Web applications design. Topics include threats and counter measures, security in Web service frameworks, session control, access control, and data protection.
CS-612 Ethical HackingCredits: 3
Prerequisite(s): CS-518
Course Type(s): CISEL
Introduce penetration testing methodologies and ethical hacking tools. Discuss the importance of protecting corporate and government data from cyber-attacks. Learn advanced computer security resources that address new vulnerabilities and innovative methods to protect networks.
CS-613 Digital ForensicsCredits: 3
Prerequisite(s): CS-518.
Term Offered: Spring Term
Course Type(s): CISEL
Introduce digital forensic fundamentals. Focus on discovering, authenticating, and analyzing digital evidence.
CS-618 Data MiningCredits: 3
Prerequisite(s): CS-517 and CS-520 both passed with a grade of B- or higher.
Term Offered: Spring Term
Course Type(s): CISEL
An introduction to the fundamental concepts, algorithms, and techniques of data mining. Topics include: data preprocessing, classification algorithms and techniques, anomaly detection, and the design of data warehousing and OLAP systems.
CS-620 Applied Machine LearningCredits: 3
Prerequisite(s): CS-503
Term Offered: All Terms
Course Type(s): CISEL
This course introduces basic and advanced machine learning techniques via various applications in finance, healthcare, image recognition and other fields. Topics include classification and regression supervised learning algorithms, unsupervised learning algorithms, and algorithm performance evaluation and validation.
CS-625 Internet CrawlerCredits: 3
Prerequisite(s): CS-529 passed with a grade of B- or higher
Term Offered: Spring Term
Course Type(s): CISEL
In-depth coverage of the crawler component of modern search engines. Examination of the architecture of crawlers; algorithms for visitation, retrieval and processing of Web pages, and link analysis (e.g., PageRank computation). Coverage of ethical and legal issues of customized Web robots. Students build automatic Internet crawlers.
CS-628 Security of E-Systems and NetworksCredits: 3
Prerequisite(s): CS-518 passed with a grade of B- or higher
Term Offered: Spring Term
Course Type(s): CISEL
The fundamental techniques in security of e-based Systems and Computer Networks. E-based systems are ubiquitous in the modern world with applications spanning e-commerce, e-government, e-services, Virtual Private Networks (VPNs), health care, and government organizations. Deals with the fundamental concepts and tools of security of e-based systems and computer networks and its range of applications. The topics to be covered include: authentication of users, system integrity, confidentiality of communication, availability of business service, non-repudiation of transactions, public key cryptosystems, authentication and digital signature, e-security tools such as Public Key Infrastructure (PKI) systems, biometric-based security systems, trust management systems in communication networks, intrusion detection systems, protecting against malware, and computer network security risk management. Intended for graduate students in computer science, software engineering, and electrical engineering who have some background in computer networks and fundamentals of computer security.
CS-635 Wireless Network Systems and SecurityCredits: 3
Prerequisite(s): CS-514 passed with a grade of B- or higher
Term Offered: Spring Term
Course Type(s): CISEL
Fundamental techniques in the design, operation, performance evaluation, and security of wireless network systems. Among the topics covered are first, second, third, and fourth generation wireless systems, cellular wireless networks, medium access techniques, physical layer, protocols (AMPS, IS-95, IS-136, GSM, GPRS, EDGE, WCDMA, cdma2000, etc.), fixed wireless systems, personal area networks (PANs) including Bluetooth and Home RF systems, wireless local area network(WLAN) technologies, architectures, protocols, and standards, and advanced topics. Security of WLANs, wireless sensor networks (WSNs), cellular systems, and Bluetooth and Home RF networks will be dealt with as well. Intended for graduate students in computer science, software engineering, and electrical engineering who have some background in computer networks.
CS-640 Real-Time Robot ControlCredits: 3
Prerequisite(s): CS-501A.
Term Offered: Spring Term
Course Type(s): CISEL
Fundamentals of real-time and embedded software technology. Inter-process communication and synchronization. Robot operatingsystem. Modern robot programming toolkits. Robot movement control. Robot speech and vision-based object recognition.
CS-650 Software Project ManagementCredits: 3
Term Offered: Fall Term
Course Type(s): CISEL
Project management techniques and their application to the management of software projects. How to develop a softwaredevelopment plan and its associated tasks, milestones and deliverables. Software project scheduling and the establishment ofrelationships among the different tasks. Tasks, dependencies and conflict resolution. Resource management and allocation. Softwareproject cost estimation. Algorithmic models for estimating costs: the COCOMO model and its derivatives. Risk assessment and itsimpact in the planning and scheduling of software projects. Software project measurement and tracking. Comparative review ofsoftware tools for software project management. Software configuration management and its importance in the management of largesoftware projects.
CS-655 Cloud Computing - Concepts, Technology and ArchitectureCredits: 3
Prerequisite(s): CS-503 passed with a grade of B- or better.
Term Offered: Summer Term
Course Type(s): CISEL
This course will introduce students to proven and mature cloud computing technologies and practices into a series of well-defined concepts, models, and technology mechanisms and architectures. Case studies will be presented to applying the concepts to practical applications.
CS-661 Computer Science Advanced ProjectCredits: 3
Term Offered: All Terms
Course Type(s): CISEL
A challenging project, such as the development of a large, complex program, done under the supervision of a faculty member.
CS-691 Computer Science Thesis ICredits: 3
Term Offered: All Terms
Course Type(s): None
Independent investigation of special topics reflecting the research interests of the sponsoring professor. Provides students with an opportunity to do extended relevant research in collaboration with, or under the supervision of, a faculty member. Sequential registration of one or more credits is required until successful completion. (Minimum of six credits must be accumulated.) Completion of all foundation and core courses and departmental approval is required to take this course.
CS-692 Computer Science Thesis IICredits: 3
Prerequisite(s): CS-691
Term Offered: All Terms
Course Type(s): None
Independent investigation of special topics reflecting the research interests of the sponsoring professor. Provides students with an opportunity to do extended relevant research in collaboration with, or under the supervision of, a faculty member. Sequential registration of one or more credits is required until successful completion. (Minimum of six credits must be accumulated.)
CS-698 Advanced Special TopicsCredits: 3
Prerequisite(s): CS-503 passed with a grade of B- or higher or as announced in the course schedule
Course Type(s): CISEL
The advanced subject matter varies with the interest of the students and of the professor. The full syllabus for a specific offering will be filed with the STE and Graduate School Deans when it is scheduled. The exact nature of the topic covered in any given semester is indicated in the student's transcript.
CS-699 Independent Study in Computer ScienceCredits: 3
Term Offered: All Terms
Course Type(s): CISEL
Independent study of a subject not substantially treated in a regular graduate course. Designed for students with superior abilities who, with guidance and direction from the supervising faculty member, can master a new subject. (Limited to students who have not yet taken CS-699.) A minimum G.P.A. of 3.50, completion of all foundation and core courses and departmental approval are required to take the course.
DS-501 Probability and Statistics for Data ScienceCredits: 3
Term Offered: Fall Term
Course Type(s): None
This course covers the process of statistical analysis from beginning to end. That process, in broad strokes, involves: posing a question, determining what experiments or observations might provide data for answering that question, developing data collection procedures, exploring and summarizing the resulting data, and deriving inferences from the data relevant to the original scientific question. Each of these steps involves one or more of the following topics that will be covered in this course: experimental design, descriptive statistics, probability models, inferential statistics, confidence intervals, hypothesis tests, and prediction. A special emphasis will be given to common pitfalls in statistical analyses in a data-science context, including common misinterpretations of statistical procedures, the confusion of association and causation, and the reproducibility crisis in science.
DS-502 Introduction to Computer Programming for Data Science ICredits: 3
Term Offered: All Terms
Course Type(s): None
Introduction to the basic concepts of program development using Python; problem-solving methods and algorithm development; basic data types; language syntax; style and documentation; and coding and testing of programs.
DS-503 Introduction to Computer Programming for Data Science IICredits: 3
Prerequisite(s): DS-502
Course Type(s): None
This course introduces the most important data structures available in R and Python and their application to several real-world domains. Methodologies to import data from external sources (files, databases, on-line resources), to manipulate and transform data, and to save\export data to data repositories are described. The course also describes how to compute descriptive statistics and how to build charts for effective data visualization tasks. The students will become familiar in using R and Python data analysis libraries.
DS-504 Database ManagementCredits: 3
Term Offered: All Terms
Course Type(s): None
Overview of database system concepts; data modeling; entity-relationship diagrams; relational database schema definition; database design; query languages; introduction to NoSQL and comparison between relational and non-relational databases; hands-on experience of SQL, Oracle, and NoSQL.
DS-510 Experimental Design and Causal InferenceCredits: 3
Prerequisite(s): DS-501
Course Type(s): None
This course introduces a rigorous, statistical definition of a causal effect, and methods for inferring causal effects from both experimental and observational data. Case studies and projects will be used to introduce students to real-world applications of experimental design and causal inference. Topics include randomized experiments (A/B testing, and its generalizations), methods for subgroup analysis in randomized experiments, graphical models for reasoning about causality, and methods for deriving causal inferences from observational data with confounders. Practical considerations (statistical power, sample size determination, design and use of pilot studies, etc.) and common pitfalls of applying these methods to real-world data will be emphasized.
DS-512 Data Analysis Solutions Using Low Code No CodeCredits: 3
Prerequisite(s): DS-501.
Term Offered: All Terms
Course Type(s): None
This course is designed for students across various disciplines who want to develop practical AI/ML and analytics skills using low-code, no-code software platforms. The course will provide the foundation for becoming an AI&ML analyst by utilizing powerful and user-friendly AI&ML software like Orange Data Mining and Dataiku.
DS-517 Ethics and Bias in AICredits: 3
Prerequisite(s): DS-502
Term Offered: All Terms
Course Type(s): CISEL
This course examines the full range of issues around BIAS and Ethics implications in AI/ML-enabled systems. Important topics include AI transparency, Fairness, BIAS, and Privacy & Security principles. Additionally, the course will cover a wide range of global AI regulatory proposed frameworks, including explainable AI techniques using SHAP and LIME techniques.
DS-520 Data Analytics: Concepts and TechniquesCredits: 3
Prerequisite(s): DS-501, DS-502, and DS-504
Term Offered: Fall Term
Course Type(s): None
This course is designed to introduce students to the discipline of data analytics and teach them basic algorithms, methodologies and techniques for data analysis. The course introduces the main steps of a data analysis process, including data gathering and collection, exploratory data analysis, data mining algorithms and methodologies for evaluating results. The most important data mining techniques, i.e. classification, regression, association and clustering analysis, are introduced. The students will gain familiarity with R and Python data analysis libraries.
DS-525 Interactive Storytelling with DataCredits: 3
Term Offered: Fall Term
Course Type(s): IM, TPS, CORTP
Designed to introduce students to the world of data journalism and teach them to tell interactive stories using raw data. We will start from asking what is data journalism and how we find stories in the data. Students will learn how to acquire data from the web, normalize the data into databases and finally use software to tell engaging, interactive stories with collected data. Students will also learn how to collect data from traditional sources that aren't necessarily found online. Students are expected to complete a data-driven journalism project as part of the course. Also offered as a undergraduate course, CO-492. Also listed as CO-592.
DS-530 Big Data Analysis, Methodologies and InfrastructuresCredits: 3
Prerequisite(s): DS-520
Course Type(s): None
This course introduces the most important algorithms and frameworks for Big Data analysis. The course will introduce fundamentals concepts of Big Data, parallel and distributed data analysis models and the most important Big Data processing frameworks currently in use. Each topic will be illustrated by examples from a different application area. The students will become familiar in using Hadoop MapReduce and Spark, which have been emerging as the most important Big Data processing frameworks currently used in research and commercial tasks. Students are expected to complete a Big Data analysis project as part of the course.
DS-535 Data Science ConsultingCredits: 1.5
Prerequisite(s): DS-501
Term Offered: Spring Term
Course Type(s): None
This course introduces the roles and responsibilities of a data scientist working with teams of non-data scientists or non-technical clients, with an emphasis on verbal, non-verbal, and written communication between the data scientist and the client throughout the entire consulting process. The unique responsibilities of a data scientist in terms of accurately conveying the limitations of a data set and data analysis technique in the context of the client's original problem will be a central topic. The course will proceed through a series of case studies which will be used to practice interviewing, writing reports, and presenting results to a client.
DS-588 Data Science Practice and ExperienceCredits: 1
Prerequisite(s): Completion of 9 credits from subject DS
Term Offered: All Terms
Course Type(s): OL
Provides opportunity for Data Science graduate students to obtain related experience in employment at a local company or institution with Monmouth University sponsorship. Available to Computer Science graduate students who have completed at least nine credit hours of graduate courses (500 level), with a minimum GPA of 3.00. Does not satisfy elective requirements. Students may take the course a maximum of two times. This is a pass/fail course. Departmental approval is required to take this course.
DS-615 Natural Language Processing for Data ScienceCredits: 3
Prerequisite(s): DS-520.
Term Offered: All Terms
Course Type(s): None
Natural language processing, shortened to NLP, is the machine learning technique to derive insights from unstructured data. Theoretical foundation in understanding textual data, statistical analysis of text data using Machine Learning and hands-on python exercises using NLP techniques for Text classification, Topic modeling, Text summarization, and Sentiment analysis using data from Twitter, website scrapping, and Amazon product review.
DS-650 Applications for Data ScienceCredits: 3
Prerequisite(s): DS-520
Term Offered: Spring Term
Course Type(s): None
This course provides students with a project to fully engage their data science skills. Projects will come from a real-world domain such as business applications (marketing, business analytics finance, insurance), health care analytics, bioinformatics, genomics, environmental analytics, social networks, data journalism, sports analytics, etc. Students will typically work with an external client to define the scope of the project, and then employ appropriate data science techniques to solve the established problems. The course will end with oral and written presentations of the project outcomes. This course is repeatable for credit.
DS-655 Advanced Data Science TechniquesCredits: 3
Prerequisite(s): DS-520 and DS-530.
Course Type(s): None
This course introduces advanced algorithms, methodologies and techniques for data analysis, with specific focus on classification, regression, clustering and association analysis. Among the most relevant algorithms, the course will cover advanced techniques, such as, deep learning, sequential pattern analysis, mixture models and grid-based clustering algorithms. Several examples, based on real-world datasets, will illustrate a variety of practical domains in which such techniques are used. Students will develop their exercises using R and Python data analysis libraries. Students are expected to complete a data-analysis project as part of the course.
DS-660 Management Science and Business AnalyticsCredits: 3
Prerequisite(s): BM-518 and BM-519
Course Type(s): MBA.Q
Provides a graduate school introduction to the methodology and tools of Management Science and Business Analytics that are a necessity for all of today's managers. Students will learn how to model, design and analyze systems. Excel will be used for quantitative analysis and decision- making tools. Students will also learn how to organize, sort and sift through high levels of data in order to make a decision. Also listed as BM-620.
DS-691 Data Science Thesis ICredits: 3
Term Offered: All Terms
Course Type(s): None
Independent investigation of special topics reflecting the research interests of the sponsoring professor. Provides students with an opportunity to do extended relevant research in collaboration with, or under the supervision of, a faculty member. Completion of all foundation and core courses and departmental approval is required to take this course.
DS-692 Data Science Thesis IICredits: 3
Prerequisite(s): DS-691
Term Offered: All Terms
Course Type(s): None
Independent investigation of special topics reflecting the research interests of the sponsoring professor. Provides students with an opportunity to do extended relevant research in collaboration with, or under the supervision of, a faculty member. Sequential registration of one or more credits is required until successful completion. (Minimum of six credits must be accumulated.)
MIS-514 NetworksCredits: 3
Prerequisite(s): CS-501A
Term Offered: All Terms
Course Type(s): CISEL
An introductory-level course on the hierarchy of networking software and hardware. Particular emphasis on Medium Access Control, Network layer, Transport layer, and Session layer. Several MAC-layer protocols, TCP/IP. Also listed as CS-514.
MIS-517 Database Design and ManagementCredits: 3
Prerequisite(s): CS-503 passed with a grade of B or higher
Term Offered: All Terms
Course Type(s): None
Introduction to database systems, data modeling, design theory and methodologies, query languages and query processing. Coverage of relational database model and design, normalization process, SQL, hands-on database design and application development. Also listed as CS-517.
MIS-565 Software System RequirementsCredits: 3
Prerequisite(s): CS-501A, SE-505, and SE-511
Term Offered: All Terms
Course Type(s): None
Students will learn advanced methods in software systems requirements. Ideally, these methods should be applied at the system, enterprise or global levels of software development. Methods in requirements elicitation, modeling of enterprises, prioritization and negotiation of requirements will be emphasized. Methods for including COTS into system applications and product families will be introduced. By the end of the course, students will master the standard documentation of system requirements. Many opportunities for hands-on experience with requirement tools will be provided throughout the course. For MSIS students only.
MIS-575 Software Verification, Validation and MaintenanceCredits: 3
Prerequisite(s): CS-501A and SE-505
Term Offered: All Terms
Course Type(s): None
Explores the techniques employed to insure quality in a software product developed in a controlled and disciplined environment. Detailed examination of software testing and inspection principles and methodologies. Provides specific methods for test case selection and inspection development leading to optimization of resource management in the software environment. For MSIS students only.
MIS-588 Information Systems Practice and ExperienceCredits: 1
Term Offered: All Terms
Course Type(s): None
Provides opportunity for international Information Systems graduate students on an F1 student visa to obtain related experience via employment at a local company or institution, with Monmouth University sponsorship. Available only to Information Systems graduate students who have completed at least 18 credit hours of graduate courses (500-600 level), with a minimum G.P.A. of 3.00. This course does not satisfy elective requirements. Students may take this course a maximum of two times. Limited to MSIS students on an F1 Student Visa. This is a pass/fail course.
MIS-599 Independent Study in Management Information SystemsCredits: 3
Prerequisite(s): #12 credits in Management Information Systems
Term Offered: Fall Term
Course Type(s): None
The development and execution of a significant research project designed by the student in consultation with a management information systems professor. This is an experience meant to focus learning on an area of special interest to the student. Prior permission of the directing professor and department chair is required to take this course.
MIS-691 Management Information System Thesis ICredits: 3
Prerequisite(s): BM-520, MIS-525, MIS-565 and either MIS-517 and MIS-514 and MIS-575 or BM-565 and MIS-550 and MIS-551
Term Offered: All Terms
Course Type(s): None
First semester of independent research in management information systems, spanning a period of two consecutive semesters in an area not substantially covered in a regular course offering, under the supervision of a faculty member. A formal thesis is required. An oral defense of the thesis before a committee of two faculty members who teach MIS courses, plus the advising professor is required. Depending on the topic, a reviewer from outside the program faculty may be asked to serve as a committee member. For MSIS students only.
MIS-692 Management Information System Thesis IICredits: 3
Prerequisite(s): MIS-691
Term Offered: All Terms
Course Type(s): None
Second semester of independent research in management information systems, spanning a period of two consecutive semesters in an area not substantially covered in a regular course offering, under the supervision of a software engineering faculty member. A formal thesis is required. An oral defense of the thesis before a committee of two faculty members who teach MIS courses, plus the advising professor is required. Depending on the topic, a reviewer from outside the program faculty may be asked to serve as a committee member. For MSIS students only.
MIS-695A Management Information System Practicum ICredits: 3
Prerequisite(s): BM-520 or MIS-623 and MIS-525 and MIS-565
Term Offered: All Terms
Course Type(s): None
A two-semester course sequence with major emphasis on a hands-on, team-oriented software development project. Students will be asked to form groups of three to five persons, which will work as a team whose purpose will be propose, plan, develop and market a software product. The teamwork exercise will be accompanied by readings, lectures and seminar discussions on economics, organizational behavior and management, managerial and financial accounting, finance, marketing, quantitative business modeling, electronic commerce, logistics, ethics, law and social responsibility. For MSIS students only.
MIS-695B Management Information System Practicum IICredits: 3
Prerequisite(s): MIS-695A
Term Offered: All Terms
Course Type(s): None
A two-semester course sequence with major emphasis on a hands-on, team-oriented software development project. Students will be asked to form groups of three to five persons, which will work as a team whose purpose will be to propose, plan, develop and market a software product. The teamwork exercise will be accompanied by readings, lectures and seminar discussions on economics, organizational behavior and management, managerial and financial accounting, finance, marketing, quantitative business modeling, electronic commerce, logistics, ethics, law and social responsibility. For MSIS students only.
MIS-699 Individual Research Project in Management Information SystemsCredits: 1-3
Term Offered: Spring Term
Course Type(s): None
The development and execution of a significant research project designed by the student in consultation with a Management Information Systems professor. An experience meant to focus learning on an area of special interest to the student. Prior permission of the directing professor and department chair is required to take this course.
SE-598 Special Topics in Software EngineeringCredits: 1-3
Course Type(s): None
The subject matter varies with the interest of the students and of the professor teaching the course. The exact nature of the topic covered in any given semester is indicated in the student's transcript.
SE-599 Independent Study in Software EngineeringCredits: 1-3
Prerequisite(s): Completion of at least 12 credits in Software Engineering
Term Offered: All Terms
Course Type(s): None
The development and execution of a significant research project designed by the student in consultation with a software engineering professor. This is an experience meant to focus learning on an area of special interest to the student. Prior permission of the directing professor and department chair is required to take this course.
SE-611 Secure Web Services DesignCredits: 3
Prerequisite(s): SE-565
Term Offered: Spring Term
Course Type(s): None
Web applications present a complex set of security issues for architects, designers, and developers. The most secure and hack-resilient Web applications are those that have been built from the ground up with security in mind. This course focuses on principles of secure Web applications design. Topics include threats and counter measures, security in Web service frameworks, session control, access control, and data protection.
SE-655 Cloud Computing - Concepts, Technology and ArchitectureCredits: 3
Prerequisite(s): CS-503
Term Offered: Summer Term
Course Type(s): CISEL
This course will introduce students to proven and mature cloud computing technologies and practices into a series of well-defined concepts, models, and technology mechanisms and architectures. Case studies will be presented to applying the concepts to practical applications. Also listed as CS-655.
SE-698 Special Topics in Software EngineeringCredits: 3
Term Offered: All Terms
Course Type(s): None
The subject matter varies with the interest of the students and of the professor teaching the course. The exact nature of the topic covered in any given semester is indicated in the student's transcript. Approval of the department is required to take this course. If a prerequisite is required it will be announced in the course schedule.
SE-699 Individual Research Project in Software EngineeringCredits: 3
Term Offered: All Terms
Course Type(s): None
The development and execution of a significant research project designed by the student in consultation with a software engineering professor. An experience meant to focus learning on an area of special interest to the student. Prior permission of the directing professor and department chair is required to take this course.
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