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MET CS 520: Information Structures with Java
This course covers the concepts of object-oriented approach to software design and development using the Java programming language. It includes a detailed discussion of programming concepts starting with the fundamentals of data types, control structures methods, classes, applets, arrays and strings, and proceeding to advanced topics such as inheritance and polymorphism, interfaces, creating user interfaces, exceptions, and streams. Upon completion of this course the students will be able to apply software engineering criteria to design and implement Java applications that are secure, robust, and scalable. Prereq: MET CS 200; Not recommended for students without a programming background. Or Instructor's Consent.
MET CS 521: Information Structures with Python
This course covers the concepts of the object-oriented approach to software design and development using the Python programming language. It includes a detailed discussion of programming concepts starting with the fundamentals of data types, control structures methods, classes, arrays and strings, and proceeding to advanced topics such as inheritance and polymorphism, creating user interfaces, exceptions and streams. Upon completion of this course students will be capable of applying software engineering principles to design and implement Python applications that can be used in conjunction with analytics and big data.
MET CS 532: Computer Graphics
This course is primarily the study of design of graphic algorithms. At the end of the course you can expect to be able to write programs to model, transform and display 3- dimensional objects on a 2-dimensional display. The course starts with a brief survey of graphics devices and graphics software. 2-d primitives such as lines and curves in 2- d space are studied and a number of algorithms to draw them on a rectangular surface are introduced, followed by a study of polygons, scan conversion and other fill methods. Attributes of the primitives are studied as well as filtering and aliasing. Geometric transformations in 2 dimensions are introduced in homogeneous coordinates, followed by the viewing pipeline, which includes clipping of lines, polygons and text. Hierarchical graphics modeling is briefly studied. The graphics user interface is introduced and various input functions and interaction modes are examined. 3-d graphics is introduced through object representations through polygonal methods, spline techniques, and octrees. This is followed by 3-d transformations and the 3-d viewing pipeline. The course ends with a study of algorithms to detect the visible surfaces of a 3-d object in both the object space and the image space. Laboratory Course. Prereq: MET CS 248 and MET CS 341 or MET CS 342. Or instructor's consent.
MET CS 535: Computer Networks
Overview of data communication and computer networks, including network hardware and software, as well as reference models, example networks, data communication services and network standardization. The OSI and the Internet (TCP/IP) network models are discussed. The course covers each network layer in details, starting from the Physical layer to towards the Application layer, and includes an overview of network security topics. Other topics covered include encoding digital and analog signals, transmission media, protocols. circuit, packet, message, switching techniques, internetworking devices, topologies. LANs/WANs, Ethernet, IP, TCP, UDP, and Web applications. Labs on network analysis. Prereq: MET CS 575 and MET CS 201 or MET CS 231 or MET CS 232. Or instructor's consent. Restrictions: This course may not be taken in conjunction with MET CS 625 or MET CS 425 (undergraduate). Only one of these courses can be counted towards degree requirements.
MET CS 544: Foundations of Analytics
The goal of this course is to provide students with the mathematical and practical background required in the field of data analytics. Starting with an introduction to probability and statistics, the R tool is introduced for statistical computing and graphics. Different types of data are investigated along with data summarization techniques and plotting. Data populations using discrete, continuous, and multivariate distributions are explored. Errors during measurements and computations are analyzed in the course. Confidence intervals and hypothesis testing topics are also examined. The concepts covered in the course are demonstrated using R. Laboratory Course. Prereq: MET CS 546 or equivalent knowledge, or instructor's consent.
MET CS 546: Quantitative Methods for Information Systems
The goal of this course is to provide Computer Information Systems students with the mathematical fundamentals required for successful quantitative analysis of problems in the field of business computing. The first part of the course introduces the mathematical prerequisites for understanding probability and statistics. Topics include combinatorial mathematics, functions, and the fundamentals of differentiation and integration. The second part of the course concentrates on the study of elementary probability theory, discrete and continuous distributions. Prereq: Academic background that includes the material covered in a standard course on college algebra or instructor's consent.
MET CS 555: Data Analysis and Visualization
This course provides an overview of the statistical tools most commonly used to process, analyze, and visualize data. Topics include simple linear regression, multiple regression, logistic regression, analysis of variance, and survival analysis. These topics are explored using the statistical package R, with a focus on understanding how to use and interpret output from this software as well as how to visualize results. In each topic area, the methodology, including underlying assumptions and the mechanics of how it all works along with appropriate interpretation of the results, are discussed. Concepts are presented in context of real world examples. Recommended Prerequisite: MET CS 544 or equivalent knowledge, or instructor's consent.
MET CS 561: Financial Informatics
This course presents financial algorithms used in applications of computer science in financial decision analysis, risk management, data mining and market analysis, and other modern business processes. The course covers theoretical background on probabilistic methods used for financial decision making and their application in number of fields such as financial modeling, venture capital decision making, operational risk measurement and investment science. Number of financial applications and algorithms are being presented for portfolio risk analysis, modeling real options, venture capital decision making, etc. The course concludes with algorithms for financial risk assessment and presents the security concepts and challenges of financial information systems.
MET CS 565: Advanced Java Programming
Undergraduate Prerequisites: MET CS 342; or equivalent knowledge of Java or instructor's consent.
Comprehensive coverage of object-oriented programming with cooperating classes. Implementation of polymorphism with inheritance and interfaces and in Java library containers. Programming with exceptions, stream input/output and graphical AWT and Swing components. Threads, sockets, datagrams and database connectivity are also covered in this course. Laboratory course.
MET CS 566: Analysis of Algorithms
Undergraduate Prerequisites: MET CS 248; and (CS341 or CS342) or instructor's consent
Discusses basic methods for designing and analyzing efficient algorithms emphasizing methods used in practice. Topics include sorting, searching, dynamic programming, greedy algorithms, advanced data structures, graph algorithms (shortest path, spanning trees, tree traversals), matrix operations, string matching, NP completeness.
MET CS 570: Biomedical Sciences and Health IT
This course is designed for IT professionals, and those training to be IT professionals, who are preparing for careers in healthcare-related IT (Health Informatics). This course provides a high-level introduction into basic concepts of biomedicine and familiarizes students with the structure and organization of American healthcare system and the roles played by IT in that system. The course introduces medical terminology, human anatomy and physiology, disease processes, diagnostic modalities, and treatments associated with common disease processes. IT case studies demonstrate the key roles of health informatics and how IT tools and resources help medical professionals integrate multiple sources of information to make diagnostic and therapeutic decisions.
MET CS 575: Operating Systems
Undergraduate Prerequisites: MET CS 472; and (CS 231 or CS 232) or instructor's consent
Overview of operating system characteristics, design objectives, and structures. Topics include concurrent processes, coordination of asynchronous events, file systems, resource sharing, memory management, security, scheduling and deadlock problems.
MET CS 579: Database Management
This course provides a theoretical yet modern presentation of database topics ranging from Data and Object Modeling, relational algebra and normalization to advanced topics such as how to develop Web-based database applications. Other topics covered - relational data model, SQL and manipulating relational data; applications programming for relational databases; physical characteristics of databases; achieving performance and reliability with database systems; object-oriented database systems. Prereq: MET CS 231 or MET CS 232; or instructor's consent.
MET CS 580: Health Informatics
This course presents the technological fundamentals and integrated clinical applications of modern Biomedical IT. The first part of the course covers the technological fundamentals and the scientific concepts behind modern medical technologies, such as digital radiography, CT, nuclear medicine, ultrasound imaging, etc. It also presents various medical data and patient records, and focuses on various techniques for processing medical images. This part also covers medical computer networks and systems and data security and protection. The second part of the course focuses on actual medical applications that are used in health care and biomedical research. Prerequisite: MET CS 570 Biomedical Sciences and Health IT, or comparable knowledge of health sciences and fundamentals of IT with instructor's consent. [ 4 cr.]
MET CS 581: Electronic Health Records
Electronic Health Records (EHRs) are application systems that automate the activities of healthcare clinicians including physicians, nurses, physician assistants, and healthcare administrative staff. Use of EHRs is increasing rapidly due to the systems' benefits and federal government programs to deploy EHRs. This increased use of EHRs has many challenges including complex data, high security requirements, integration to multiple application systems, a distributed user base, and broad impact on how these users work.
MET CS 593: Special Topics
Prereq: consent of the instructor.
MET CS 599: Biometrics
In this course we will study the fundamental and design applications of various biometric systems based on fingerprints, voice, face, hand geometry, palm print, iris, retina, and other modalities. Multimodal biometric systems that use two or more of the above characteristics will be discussed. Biometric system performance and issues related to the security and privacy aspects of these systems will also be addressed.
MET CS 601: Web Application Development
MET CS 625: Business Data Communication and Networks
This course presents the foundations of data communications and takes a bottom-up approach to computer networks. The course concludes with an overview of basic network security and management concepts. Prereq: MET CS 200, or instructor's consent. This course may not be taken in conjunction with MET CS 425 (undergraduate) or MET CS 535. Only one of these courses can be counted towards degree requirements.
MET CS 632: Information Technology Project Management
This course provides students with a comprehensive overview of the principles, processes, and practices of software project management. Students learn techniques for planning, organizing, scheduling, and controlling software projects. There is substantial focus on software cost estimation and software risk management. Students will obtain practical project management skills and competencies related to the definition of a software project, establishment of project communications, managing project changes, and managing distributed software teams and projects.