Course Description

Course Code: CSE 5001
Credit Hour: 3.00
Prerequisite:

Introduction to programming and logic flow, procedural versus object oriented programming, data types, variables, constants, operators, expressions, input-output, control structures, arrays, functions, pointers, file access, structures, dynamic memory allocation, classes, objects, constructor and destructor, access modifiers, inheritance, polymorphism, multiple inheritance, friend functions, virtual class, files and streams, user interface design, exception handling.

Course Code: CSE 5031
Credit Hour: 3.00
Prerequisite:

Introduction to elementary data structures and their usages: Arrays, records, linked lists, stack and queue; Basic searching and sorting techniques; Cost and performance analysis of algorithms; Trees and graphs; Traversal techniques of trees and graphs; Recursion, divide and conquer techniques; Greedy method; Dynamic programming; Graph algorithms; Hashing; A survey of hard problems; NP-completeness and intractable problems.

Course Code: 3.00
Credit Hour:
Prerequisite:

Introduction to database, data models: Entity-relationship model and relational model, functional dependency, normalization, relational algebra, SQL: Basic and complex query, joining; Database design and implementation on DBMS, indexing, data integrity and security, database storage and file structure, transaction management, concurrency control, recovery management, object-oriented database and XML.

Course Code: CSE 5029
Credit Hour: 3.00
Prerequisite:

Introduction to data communication and networks; transmission media, signals, noises, modulation and demodulation, encoding; Data networks, single and multichannel data communication, circuit switching and packet switching. Network architecture, layering and protocols, OSI reference model, TCP/IP architecture; LAN concepts, media, collision and broadcast; MAC address, framing, token ring, Fiber Distributed Data Interface (FDDI), Ethernet and Carrier Sense Multiple Access Collision Detection (CSMA/CD), IEEE 802.3; Routing, IP address, ARP and RARP, DHCP, RIP, IGRP and EIGRP, OSPF; Transport layer; Session layer; Presentation layer; Application layer.

Course Code: CSE 5013
Credit Hour: 3.00
Prerequisite:

Information, general concepts of formal information systems, analysis of information requirements for modern organizations, modern data processing technology and its application, information systems structures, designing information outputs, classifying and coding data, physical storage media considerations, logical data organization, systems analysis, general systems design, detail system design, Project management and documentation, Group development of an information system project: includes all phases of software life cycles from requirement analysis to the completion of a fully implemented system.

Course Code: CSE 5013
Credit Hour: 3.00
Prerequisite:

Information, general concepts of formal information systems, analysis of information requirements for modern organizations, modern data processing technology and its application, information systems structures, designing information outputs, classifying and coding data, physical storage media considerations, logical data organization, systems analysis, general systems design, detail system design, Project management and documentation, Group development of an information system project: includes all phases of software life cycles from requirement analysis to the completion of a fully implemented system.

Course Code: CSE 5019
Credit Hour: 3.00
Prerequisite:

Overview, Structure of C program, Data Types, I/O Functions, Identifiers, Expressions, Statement and Symbolic Constants, Arithmetic operators, Relational Operators and Logical Operators, Bit-wise Operators, Precedence and Associativity, Control statements, Storage class, Functions, Command Line Parameters and Library Functions, Arrays, Strings, Structure, Union and Bit-fields, Pointer, Memory Allocation and Release, Pointer and Multi-Dimensional Arrays, File Handling, Video Adapter, Modes and Graphics Initialization, Graphics Functions.

Course Code: CSE 5021
Credit Hour: 3.00
Prerequisite:

Frequency distribution. Mean, median, mode and other measures of central tendency. Standard deviation and other measures of dispersion. Moments, skewness and kurtosis, correlation and regression analysis. Elementary probability theory and discontinuous probability distribution, e.g., binomial, Poisson and negative binomial. Continuous probability distributions, e.g. normal and exponential. Characteristics of distributions. Elementary sampling theory. Estimation of parameter, Hypothesis testing, Index number. Time series analysis and Markov chain.

Course Code: CSE 5023
Credit Hour: 3.00
Prerequisite:

Survey and concepts in Artificial Intelligence, Problem solving agents, Uninformed and Informed search techniques, Game playing, Knowledge representation, Inference in Propositional and First Order logic, Theorem Proving, Decision tree learning, Neural Network, Bayesian learning, planning.

Course Code: CSE 5025
Credit Hour: 3.00
Prerequisite:

Introduction; the context of business: business practices, economic indicators, positive and negative impacts of business on society, current economic trends, business cycle in real-life situations, global trade restrictions, factors affecting the success of businesses, feasibility of doing business in a foreign country, methods for business entry into the global marketplace, trade facilitators; Entrepreneurship: potential of a business, major components of a business plan, impact of small business on the economy; Legal Forms of Business : sole proprietorships, partnerships corporations; limited-liability corporations business practices ; Marketing; Accounting, Finance, and Banking; Management.

Course Code: CSE 5027
Credit Hour: 3.00
Prerequisite:

Management Basics; Classical School of Management Theory; Organizational Change; Organizing in Business Management; Work Teams; Leading in Organizations; Leadership Theory; Motivation in the Workplace; Communication in the Workplace; Controlling in Organizations; Human Resources; Strategic Management and Managerial Decision Making; Production and Quality Assurance; International Management and Contemporary Issues; Behavioral School of Management Theory; Contemporary and Future School of Management Theory

Course Code: CSE 5033
Credit Hour: 3.00
Prerequisite:

Introduction to Health Informatics, Information Science, Computer Technology, Information Science and Computer Technology in Healthcare, Computer Based Communication Systems, Clinical Decisions, Information Retrieval, Telemedicine, Bioinformatics, evidence-based medicine.

Course Code: CSE 5035
Credit Hour: 3.00
Prerequisite:

History of Biostatistics, Biomedical Data, Data Collection, Analysis and Data Interpretation, Regression Methods, Interpret Written Data, Visual Representation of Statistical Data, Statistics, Statistical Hypothesis Testing, Variability, Normal Distribution, Summary Measures, Binary Data, Confidence Interval, Sampling, p-Value, Mis-specification and Robustness Checks, Proportional Hazards Model, Applications of Biostatistics.

Course Code: CSE 5037
Credit Hour: 3.00
Prerequisite:

Health and Disease Concept, Definitions & Dimensions of health and wellbeing, Determinants of health, Evolution of medicine, Public Health, Health indicators, Health service philosophies, Disease & causation, Natural history of disease, Disease control & prevention, Changing patterns of disease. Medical sociology –Introduction Sociological perspective of health, illness, and healing. Institutional perspective and Organizational perspective.

Course Code: CSE 6001
Credit Hour: 3.00
Prerequisite:

Database system architecture; managing primary and secondary storage; query processing; metadata and catalog management; language processing; query optimization and plan generation; concurrency; failures and recovery; extensibility; client-server interactions. Object-oriented database systems, XML, database and the web, data management in distributed mobile computing environment, data broadcasting, text database, digital library design and implementation, multimedia database: Basic concept, design and optimization of access strategies; parallel database, spatial database, temporal database.

Course Code: CSE 6003
Credit Hour: 3.00
Prerequisite:

Introduction to the requirements definition phase of software development. Models, notations, and processes for software requirements identification, representation, validation, and analysis. Systematic testing of software systems, symbolic execution, software debugging, measurement and prediction of software reliability, project management, software maintenance, software reuse, reverse engineering. Software quality, software process and process metrics, different quality metrics of software; Verification and validation tasks and techniques, software error and defect removal, SQA management and models, statistical quality control; Quality management system: ISO 9000, ISO 9001 and IEEE 12207 Standards; Compliance criteria of different standards: 9000/AS-3563 and ISO 9001, Capability Maturity Model (CMM), People Capability Maturity Model (P-CMM); Benchmarking and certification.

Course Code: CSE 6005
Credit Hour: 3.00
Prerequisite:

Introduction to Object Oriented Design, Modeling Concept: Modeling as a Design Technique, Object Modeling, Dynamic Modeling and Functional Modeling; Design Methodology: Methodology Preview, Analysis, system Design, Object Design and Comparison of Methodologies.

Design Implementation: Design Implementation, Programming Style, Object Diagram Compiler; Future of Object-Oriented Technology. In addition, the course covers areas of object storage and retrieval, distributed systems, business rules and objects and introduces architecture for supportable systems. Emphasizing productivity and quality, the course concludes with pragmatic guidelines on how to incorporate testing and quality assurance into the development process of object-oriented systems.

Course Code: CSE 6007
Credit Hour: 3.00
Prerequisite:

Concepts of Multi-Tier Applications and Components; Communication between Components; Protocols and Standards. Review of UML. Use of UML for Design of Multi-Tier Application. Design and Development of Client, Middle-Tier and Server Components. Use of Standard RAD Packages for Development of Multi-Tier Application. Use of CORBA, DCOM, VisiBroker, and other technologies to develop an N-Tier application. Use of ADO, MIDAS to create multi-tier and web server based applications.

Course Code: CSE 6009
Credit Hour: 3.00
Prerequisite:

Introduction; Advanced search techniques in AI, Advanced plan generating systems; Probabilistic Reasoning, decision networks; Making complex decisions: Sequential decision problems, partially observable Markov decision problems (POMDPs); Multiple agent theory: Cooperation among multiple agents; Learning from observations: Inductive learning, decision trees, ensemble learning; Knowledge in learning: Use of logic, explanation based learning, inductive logic programming; Statistical learning: Complete data, hidden nodes (EM method), instance based learning, neural networks and neural belief networks; Fuzzy logic and Genetic algorithm.

Course Code: CSE 6011
Credit Hour: 3.00
Prerequisite:

Introduction to data mining, data preparation, data mining primitives, language and systems, architecture, decision tree and its variants, mining association rules in large databases; classification and reduction, cluster analysis, mining complex types of data. Classification approaches such as inductive inference of decision trees and neural network learning, clustering techniques, inductive logic programming / multi-relational data mining and time series mining. The emphasis will be on algorithmic issues and data mining from a data management and machine learning viewpoint.

Course Code: CSE 6013
Credit Hour: 3.00
Prerequisite:

Introduction; Syntactic processing: Grammars and parsing, augmented grammars, grammars for natural language, parsing, ambiguity resolution; Semantic interpretation: Semantics and logical form, linking syntax and semantics, scoping; Context and world knowledge: Knowledge representation and reasoning, local discourse context and reference, using world knowledge, conversational agent.

Course Code: CSE 6015
Credit Hour: 3.00
Prerequisite:

Introduction: Statistical versus structured natural language processing (NLP), basic statistics and statistical model, linguistics essentials, corpus-based NLP; Models and techniques: Collocations, statistical Inference, word sense disambiguation, lexical acquisition, Markov models; Grammar: Part-of-speech tagging, probabilistic context free grammars, probabilistic parsing; Applications and techniques: Statistical alignment, clustering, information retrieval, text categorization.

Course Code: CSE 6019
Credit Hour: 3.00
Prerequisite:

Introduction; Modeling human speech perception: Auditory, neural and cognitive processing, pattern matching, linguistic processing; Representations of speech signal: Band-pass filter energies, formants, LPC and ARMA, cepstrum and mel-cepstrum, auditory-model based representations, difference coefficients, comparison of parametric representations; Recognition modes and modalities: Speaker dependency, isolated and continuous words, vocabulary size, speaking environment, perplexity, real-time operation; Stochastic models, linguistic models, prosodic knowledge sources; Knowledge-based approaches: Templates versus features, segmentation, labeling, fuzzy reasoning; Stochastic approaches: Hidden Markov Models (HMM), training and testing algorithms; Connectionist approaches: Neural networks, learning algorithms; Applications: Dictation systems, voice-based communications, system control, security systems, speaker verification.

Course Code: CSE 6021
Credit Hour: 3.00
Prerequisite:

Overview of pattern recognition and pattern recognition applications; Structure of a pattern recognition system, patterns and features, feature extraction, feature vector and feature space, classifiers, decision regions and boundaries, discriminant functions; Comparison of statistical pattern recognition, syntactic pattern recognition and neural pattern recognition. Introduction to formal languages; String languages for pattern description; Higher dimensional pattern grammars; Syntax analysis as a recognition procedure; Stochastic languages; Error-correcting: Parsing for string languages error-correcting; Tree automata; Cluster analysis for syntactic patterns; Grammatical inference for syntactic pattern recognition.

Course Code: CSE 6023
Credit Hour: 3.00
Prerequisite:

Introduction, Supervised and Unsupervised learning in propositional logic, Induction of decision trees, Noise and over-fitting issues, Minimum description length principle, Conceptual clustering, Version space, Nearest neighbor classifier, Genetic algorithm, Computational learning theory.

Learning in first order logic, Top-down and Bottom-up approaches for inducing first order theory, Handling noise, First order theory revision, Predicate invention, Application of Inductive Logic Programming, Multiple predicate learning, Different types of language bias, PAC Learnability, knowledge discovery in database and data mining, Text and image retrieval.

Course Code: CSE 6025
Credit Hour: 3.00
Prerequisite:

Fundamentals of Neural Networks, Back propagation and related training algorithms; Hebbian learning; Cohen-Grossberg learning; The BAM and Hopfield memory; simulated Annealing; Different types of neural networks; Counter propagation, probabilistic, radial basic function, generalized regression etc. Adaptive Resonance theory; Dynamic systems and neural control; The Boltzman machine; Self organizing maps; spatiotemporal pattern classification, The Neo-cognition, practical aspects of neural networks.

Introduction, crisp sets to fuzzy sets; Operations on fuzzy sets, fuzzy arithmetic, fuzzy relations and fuzzy relation equations; Fuzzy logic, fuzzy propositions and quantifiers, linguistic hedges, implications; Applications: Expert systems, fuzzy controllers, pattern recognition and information retrieval systems, engineering applications, medical applications.

Course Code: CSE 6027
Credit Hour: 3.00
Prerequisite:

This course covers the advanced research topics of image processing which include image data acquisition and digitization, description, enhancement, segmentation, image transforms, filtering, restoration, coding, enhancement, extraction, clustering and classification schemes, retrieval and evaluation. Students are encouraged to collect and evaluate recently published articles in the above mentioned topics.

Course Code: CSE 6277
Credit Hour: 3.00
Prerequisite:

Cyber Security in Healthcare, Cyber Security Solution for Healthcare Industry, Privacy and security regulations for healthcare information transactions including policy, procedures, guidelines, security architectures, risk assessments, disaster recovery, and business continuity; Health Insurance Portability and Accountability Act (HIPAA); Health Information Technology for Economic and Clinical Health (HITECH) Act; Privacy and confidentiality of Protected Health Information (PHI), General Data Protection Regulation (GDPR), local privacy and security laws.

Course Code: CSE 6029
Credit Hour: 3.00
Prerequisite:

Introduction to computer graphics; Viewing model; Transformations: Rotation, translation, and scaling; Rendering techniques: Scan conversion, clipping, filling polygon; Hidden line and hidden surface removal; color models, illumination and shading, texture mapping; Animation techniques: Mesh based system, skeletal animation system; Animation models, fractals. This course covers 3D viewing transformations; object hierarchy and 3D graphics standards (GL, PHIGS and others); parametric curves, surfaces, and solid modeling; visible surface determination; texture mapping and imaging; ray tracing and radioicity; advanced animation techniques. Optional topics: virtual reality issues and VRML; advanced raster algorithms and modeling techniques.

Course Code: CSE 6031
Credit Hour: 3.00
Prerequisite:

Introduction to multimedia, image, sound, video formats and their different properties, compression, playing and recording techniques, conversions between different formats and their combinations; Multimedia authoring, introduction to web and HTML, basic HTML tags design principles; Drawing: Basic image properties, image manipulation, layers, colors, text, texture, brightness, contrast, filters and effects; Application development using multimedia tools.

Course Code: CSE 6039
Credit Hour: 3.00
Prerequisite:

Web architecture and HTTP: History and architecture of the World Wide Web, overview of the Hyper Text Transfer Protocol, other related protocols; Hyper Text Markup Language: The concept of markup, overview of HTML ( table, form, frame, window, link etc.); Client side scripting: Variables, data types, control structure, functions, Document Object Model (DOM), event handlers, properties, methods, cookies; Server side scripting: Concepts, variables, data types, control structure, functions, objects; Database: Content generation, data exchange; Regular expressions, mails, cookies, sessions.

Course Code: CSE 6041
Credit Hour: 3.00
Prerequisite:

Introduction, parallel processing, parallel models, performance of parallel algorithms, work-time presentation framework; Basic techniques: Pointer jumping, balanced trees, divide and conquer, pipelining, partitioning, symmetry breaking; List ranking, Euler tour technique, tree contraction; Parallel searching, merging and sorting; Connected components; Minimum spanning trees; Bi-connected components; Simulation between PRAM models: EREW, CREW and CRCW.

Course Code: CSE 6043
Credit Hour: 3.00
Prerequisite:

Introduction, fundamental concepts; Trees: Spanning trees in graphs; Distance in graphs, Eulerian graphs, digraphs, matching and factors, cuts and connectivity, network flow problems, graph coloring: Vertex coloring and edge coloring, line graphs, planar graphs, perfect graphs. This course covers Primal graphs and other graph covering problems, The Appel-Haken proof of the four colour theorem. The perfect graph theorems and conjectures. Matching theory and / or the reconstruction conjecture revisited. Algebraic graph theory including distance regular and distance transitive graphs.

Course Code: CSE 6045
Credit Hour: 3.00
Prerequisite:

Concepts, classifications; Characteristics; Requirements; Embedded microcontroller cores; Embedded memories; Technological aspects; Interfacing between analog and digital blocks; Signal conditioning, digital signal processing, sub-system interfacing; Interfacing with external systems, user interfacing; Design trade offs, thermal considerations.

Course Code: CSE 6047
Credit Hour: 3.00
Prerequisite:

Hardware design for embedded systems; Software development for embedded systems; Network based embedded systems; Sensors and Transducers for embedded systems; Case study on advanced embedded system; Co-design using FPGAs; Multiprocessor systems; Case study on multiprocessor system; Introduction to digital control; Its embedded systems; Case study on digital control in embedded systems.

Course Code: CSE 6049
Credit Hour: 3.00
Prerequisite:

Definition of real-time, temporal and event determinism, design principles and practice; Architecture review and interfacing, interrupts, traps and events, response times and latency, real-time clocks; Operating systems: Structure of an RTOS, nucleus, servers, schedulers and dispatchers; Synchronization and communication: priority and distribution queues, system Modeling, static scheduling, priority drive scheduling; Real-time communication, device drivers, operating systems; Languages in real-time, concurrency issues, Real-time programming.

Course Code: CSE 6057
Credit Hour: 3.00
Prerequisite:

Introduction and History of Wireless Systems, Cellular Systems, Wireless LANs, Satellite Systems, Paging Systems; Radio Propagation: free space propagation, propagation mechanisms, link budget design using path loss model, outdoor propagation models, indoor propagation models; Introduction to Small-Scale Fading, Impulse response model of multipath channel, parameters of multipath channel, type of small scale fading, Rayleigh and Ricean and Distribution; Media Access Control: FDMA, TDMA, and CDMA, Aloha, CSMA, MACA;

GSM overview: Standards, Services and structure, GSM air interface physical layer: physical channels, logical channels, frame structures, modulation, coding and interleaving, GSM signaling: Data link layer, radio resource management, mobility management, Handover, location update and roaming in GSM; Short message service (SMS), circuit switched data, General Packet Radio Service (GPRS), Enhanced GPRS (EGPRS); CDMA Digital Cellular System (IS-95): Forward CDMA Channel, Reverse CDMA Channel;

Satellite mobile communications: History, Localization, Handover, Routing; Broadcast System: Unidirectional distribution systems, DAB-architecture, DVB-container; WCDMA in 3^rd generation system, Difference between WCDMA and 2G air interface, 3^rd generation standards.

Course Code: CSE 6059
Credit Hour: 3.00
Prerequisite:

Some basics on television systems, multidimensional signals and Fourier transform, multidimensional (space-time) sampling, interlaced and non-interlaced scanning: Information theory: conditional and joint entropy and redundancy, source coding theorem, statistical source models, mutual information rate distortion theory: Predictive coding: linear prediction, quantization, optimum predictor; Discrete two-dimensional transforms: DFT, DCT,. Wavelet and Hadamard transforms; Transform Coding with motion estimation, principles of MPEG coding; Modern audiovisual terminals and communication systems.

Course Code: CSE 6065
Credit Hour: 3.00
Prerequisite:

Challenges of mobile and wireless networking; Wireless LAN: infrastructure networks, IEEE 802.11: Physical layer, framing, multiple access techniques: Wireless PAN: Blue Tooth, IEEE 802. 15: Broadband wireless: Wireless ATM, 802. 16. Local Multipoint Distribution Service (LMDS), Multi channel multipoint Distribution System (MMDS), Data Over Cable System Interface Specification (DOCSIS+); Network Protocols: Motivation, mobile IP, cellular IP, Mobile Ad Hoe Networking (MANET), MIPv6; Mobile transport layer: Motivation, TCP-mechanisms, classical approaches, indirect TCP, snooping TCP, mobile TCP, optimizations: Fast retransmit/recovery, transmission freezing, selective retransmission, transaction oriented TCP, TCP for 2.5G/3G wireless: support for mobility: File systems, databases, WWW and mobility , Wireless Application Protocol (WAP), i-mode.

Course Code: CSE 6067
Credit Hour: 3.00
Prerequisite:

Application specific protocols: Domain Name Services, Electronics mail, World Wide Web and Web caching, Network Management (SNMP), Error Reporting Mechanism (ICMP), Socket Interfaces, File Transfer and Remote File Access, Multimedia application: RTP, Session Control; Network security: Cryptographic algorithm, security mechanism, authentication protocol, firewall.

Course Code: CSE 6071
Credit Hour: 3.00
Prerequisite:

VLSI technology: terminologies and trends; MOS transistor characteristics and equations; NMOS and CMOS inverters: DC and transient characteristics; Pass transistors and pass gates; CMOS layout and design rules, complex CMOS gates; Resistance and capacitance estimation and modeling; Signal propagation delay, noise margin and power consumption; CMOS building blocks: adders, counters, barrel shifters and multipliers; Data path, memory structures, PLAs and FPGAS; CMOS structured design strategy, automated synthesis, placement, routing, circuit extraction, simulation and testing; Practical chip design examples.

Course Code: CSE 6073
Credit Hour: 3.00
Prerequisite:

Basic Probability: Various definitions of probability, axioms of probability, basic properties derived from the axioms, conditional probability, total probability, Bayes’ rule, Independence of events, combined experiments and independence, binary communication channel decoding.

Random variables: Definition, cumulative distribution function (cdf), continuous, discrete and mixed random variables, probability density function (pdf), examples of random variables, physical interpretation of pdf’s (histograms), multiple random variables, joint distribution – definition and properties, joint density – definition and properties, marginal distribution and density, conditional distribution and density, independence of random variables, expectations, moments, central moments, properties of expectation operator, mean, variance, Markov inequality, Chebyshev inequality, Chernoff bound, effect of linear transformations on mean and variance, autocorrelation, cross-correlation, covariance, Cauchy-Schwartz inequality, conditional expectation, characteristic function, cental limit theorem, transformations of single and multiple random variables, random vectors, properties of Gaussian random vectors.

Random processes: Definition, stationarity, mean, correlation and covariance, wide-sense stationary random processes, examples of random processes, cross-correlation functions, joint wide-sense stationarity, time averages and ergodicity, measuremen of mean and autocorrelation function, transmission of random process through a linear filter – relationship between input and output processes, power spectral density (PSD) – definition and proporties, examples, relationship between input and output process PSD for a linear filter, periodograms, cross spectral densities, Gaussian process – properties, white noise, noise equivalent bandwidth, narrowband noise, bandpass processes – representation,sampling.

Other topics (some of these will be covered depending on time available): Cyclostationary random processes, PAM signals, Baseband shaping (raised cosine), optimum transmitting and receiving filters for noise immunity, matched filtering, sampling and expansion of random processes.

Course Code: CSE 6075
Credit Hour: 3.00
Prerequisite:

Introduction, Basic Elements, Various Uses of Satellite Communications: Traditional Telecommunications, Cellular, Television Signals: C-Band, Digital; Marine Communications, Space Bourne Land Mobile, Satellite Messaging for Commercial Jets, Global Positioning Services, Technological Overview: Error Correction-Forward-error-correction, Automatic-repeat-request, Hybrid Networks, ATM over Satellite , SATIN, VSAT Networks, Orbits: GEO, LEO, Constellations: Global Voice Communications, Global Broadband Networks

Course Code: CSE 6081
Credit Hour: 3.00
Prerequisite:

Telephone transmission, networks, ITU recommendations. Communication links: coaxial, line-of-sight (LOS) links, tropospheric scatter, millimeter wave links fibre optic links, HF, VHF and UHF radio systems. Local Area Network (LAN) fibre distributed data interface (FDDI), MAN, WAN, frame relay, narrow band ISDN (NISDN), switched multi-megabit data services (SMDS), broadband (BISDN). Mobile cellular communication systems: FDMA, TDMA, CDMA, satellite communication systems.

Course Code: CSE 6085
Credit Hour: 3.00
Prerequisite:

Explore s/w project management activities from product concept through development based upon best practices. Covered topics include software systems engineering process management and control, and project planning and management. After successful completion of the course, the student will understand how standard engineering practices applied to software products including life cycle development processes. The student will learn to manage software as a distinct project, use specifications and descriptions, make use of structured and object-oriented techniques, complete reviews and audits, confirm product development with planned verification, and validation and testing.

Course Code: CSE 6087
Credit Hour: 3.00
Prerequisite:

C# and .NET

C# is a strongly-typed object-oriented language designed to give the optimum blend of simplicity, expressiveness, and performance. The .NET platform is centered around a Common Language Runtime (similar to a JVM) and a set of libraries which can be exploited by a wide variety of languages which are able to work together by all compiling to an intermediate language (IL). C# and .NET are a little symbiotic: some features of C# are there to work well with .NET, and some features of .NET are there to work well with C# (though .NET aims to work well with many languages). This course is mostly concerned with C#, but sometimes it is useful to discuss .NET too. The C# language was built with the hindsight of many languages, but most notably Java and C++.

Course Code: CSE 6259
Credit Hour: 3.00
Prerequisite:

Direct link networks: encoding, framing, error detection, flow control, example networks; Packet switching and forwarding: bridges, switches; Internetworking: Internet Protocol, routing, addressing, IPv6; End-to-end protocols: UDP, TCP; Network Management: issues, architecture, management information base (MIB), SNMP, TMN and CMIP; Network security concepts; Application-level protocols. Wireless networks: communication overview, MAC concepts and protocols, wireless mobility, mesh and vehicular networks, sensor networks.

Course Code: CSE 6091
Credit Hour: 3.00
Prerequisite:

Classical Cryptography: Introduction to simple cryptosystems, Cryptanalysis; Shannon’s Theory: Perfect secrecy, Entropy, Product cryptosystems; Data Encryption Standard: Description of DES, Differential cryptanalysis; RSA System and Factoring: Public-key cryptography, RSA cryptosystem, Attacks on RSA, Factroing algorithms; Other Public-key cryptosystems: ElGamal cryptosystem and discrete logs, Merkle-Hellman Knapsack System; Signature Schemes: ElGamal signature schemes, Digital signature standard, Fail-stop signatures; Hash Functions: Signatures and Hash functions, Collision-free Hash functions, Birthday attack; Key Distribution and Key Agreement: Key predistribution, Kerboros, Diffie-Hellman key exchange; Identification Schemes: Schnorr identification scheme, Okamoto identification schemes; Authentication Codes: Computing deception probabilities, Combinatorial bounds, Entropy bounds; Secret Sharing Schemes: Shamir threshold scheme, Access structure and general secret sharing; Pseudo-random Number Generation: Indistinguishable probability distribution, probabilistic encryption; Zero-knowledge proofs: Interactive proof systems, computational Zero-knowledge proofs.

Course Code: CSE 6093
Credit Hour: 3.00
Prerequisite:

Introduction to research methodology: the nature of CS research, Literature searches, information gathering, Reading and understanding research papers; Technical writing: Referencing, Bibliographies; Presentation skills: Written and Oral; Quantitative methodology: Application of statistical concepts/procedures; Graphs, numerical summaries; Normal distribution, Correlation/regression analyses, Probability, Statistical inferences; Different testing methods: Hypothesis tests, Chi-square tests, etc.; Qualitative methodology: Introduction, Ethnography, Sociolinguistics, Symbolic interaction, Emphasizes observation; Technical Writing: Guidelines for effective technical writing, Principles of technical writing, Writing with greater clarity and precision, Strategies to detect weak areas and improve documents, Organizing material by purpose and audience, Tips and techniques to start writing, Improving the appearance of technical documents, Plagiarism checking.

Course Code: CSE 6095
Credit Hour: 3.00
Prerequisite:

Introduction: Complexity of Web Application, Web Crisis, Web Engineering vs Software Engineering, Web Engineering Activities; Web Engineering: Definition, Necessities of Web Engineering, Evaluation of Web Applications, Practice and Research Issues in Developing: Methodologies, Testing, Metrics and Quality, Maintenance, Constructing simulation based web documents, Web Engineering in Practice: Web application development, Web development team demographics, Web Engineering Processes, Characteristics of Web Development Projects; Web Engineering Revisited: Web Architecture, Service Oriented Architecture(SOA), Loose Coupling; Web Engineering 2.0: Engineering for Evolution, Web Evolution; Distributed Web Service Discovery Architecture: Web Service Definition Language (WSDL), Universal Description, Discovery and Integration, WCF and Simple Object Access Protocol (SOAP).

Course Code: CSE 6119
Credit Hour: 3.00
Prerequisite:

Introduction: history of wireless communication, future trends, market and business impact; Mobile IP and Wireless Access Protocols; IEEE 802.15: Radio, base band, link control, adaptation; Fundamental limits of wireless transmission: wireless channel and system models, fading and diversity, resource management and power control; Multiple-antenna and MIMO systems; GSM: services, architecture, protocols, handover, security; UMTS; Wireless LAN: 802.11, HiperLAN, Bluetooth; Mobile IP: agent discovery, registration, optimizations, tunneling and encapsulation, IP micro mobility support; TCP improvements: snooping, TCP over 2.5/3G wireless networks, Support of mobility: wireless datagram, WML Script, push-pull services, WAP 2.0; Mobile architectures and operating systems:?

Course Code: CSE 6121
Credit Hour: 3.00
Prerequisite:

Introduction to Ad-hoc Networks: Applications and motivations; Broadcasting protocols: Algorithmic aspect, Optimization techniques, Power-efficient broadcasting; Routing protocols: DSDV, AODV, DSR, load balancing, multi-path routing; Medium access control protocols: Reservation-based MAC protocols, Bluetooth technology, IEEE 802.11; Channel propagation models; Topology control protocols; Power aware protocol design; Cross layer design principles; Mobility awareness; Fairness and security issues: Attacks and preventions. Introduction to Sensor Networks: Applications; Localization and tracking: Tracking multiple objects; Medium Access Control: S-MAC, IEEE 802.15.4 and ZigBee; Attribute-Based Routing: Directed diffusion, Rumor routing, Geographic hash tables; Infrastructure establishment: Topology control, Clustering; Sensor tasking and control: Task-driven sensing, Information-based sensor tasking; Sensor network databases: Challenges, Querying the physical environment, In-network aggregation.

Course Code: CSE 6125
Credit Hour: 3.00
Prerequisite:

Internet architecture: protocol layering, benefits of layered architectures, TCP/IP vs. OSI; Internet Addressing: Internet address concept, classes of IP addresses, subnet, ARP, DNS; Transport Protocols: TCP, UDP and SCTP; Multi-streaming and multi-homing; Network and Routing: bridges, routers, switches, IP, RIP, OSPF, BGP-4; Application Level Protocols: SMTP, FTP, HTTP, SNMP; Security and Firewalls: assessing the risk, firewalls, proxies, data encryption; QoS architectures: Diff-Serv, RSVP, MPLS, RTP; Multicast Delivery: IGMP, PIM, MBONE.

Course Code: CSE 6127
Credit Hour: 3.00
Prerequisite:

Introduction: OSI security architecture, security attacks, security services; Security protocol properties: authentication, secrecy, integrity, availability, non-repudiation, atomicity, certified delivery; Different cryptographic protocols: authentication protocols, key distributions protocols, e-commerce security protocols; Key distribution and user authentication: Kerberos, X.509; Transport Layer Security: SSL, TLS, HTTPS, SSH; IP layer security: IPsec, AH, ESP, IKE; Wireless network security: IEEE 802.11i, WAP; Intrusion Detection System (IDS): host-based IDS, network based IDS, misuse detection methods, anomaly detection; Malicious Software: viruses, worms, DDoS.

Course Code: CSE 6131
Credit Hour: 3.00
Prerequisite:

The basic concepts; Stochastic local search; Meta-heuristic algorithms; Nature inspired algorithms; Multi-objective optimization; Reinforcement learning; Single-Layer and Multi-Layer Feed forward Neural Networks; Feedback Neural Networks; Associative Memories; Learning Vector Quantizer (LVQ); Self-Organizing Feature Maps; Radial Basis Function Neural Networks; Support Vector Machines; Fuzzy Sets and Fuzzy Logic; Fuzzy Neural Networks; Fuzzy ARTMAP; Feature Selection; The Power and Computational Complexity of Computational Intelligence Models.

Course Code: CSE 6135
Credit Hour: 3.00
Prerequisite:

Introduction, Semantic Web Roadmap, Semantic Documents: XML and its impact, RDF, OWL, OWL DL and RDF Rules and rest of the alphabet soup; Lightweight Semantics: Microformats, POSH, Web services; Semantic Organization: Taxonomies, Ontologies and Rules with F-Logic; F-Logic vs. RDF and F-Logic Semantics; Relations between Semantic Web Languages; User-driven Semantics: Tags, Semantic; Collaboration: Social Software, Semantic; Discovery: Information Retrieval and Agents, Semantic Visualization, Semantic Desktop, Semantic Web Vocabularies and Applications.

Course Code: CSE 6141
Credit Hour: 3.00
Prerequisite:

Searching and Geometric Data Structures: Balanced binary search trees, Priority-search trees, Range searching, Interval trees, Segment trees; Algorithms and complexity of fundamental geometric objects: Polygon triangulation and art gallery theorem, Polygon partitioning, Convex-hulls in 2-dimension and 3-dimension, Dynamic convex-hulls; Geometric intersection: Line segment intersection and the plane-sweep algorithm, Intersection of polygons; Proximity: Voronoi diagrams, Delunay triangulations, Closest and furthest pair; Visualization: Hidden surface removal and binary space partition (BSP) trees; Graph Drawings: Drawings of rooted trees (Layering, Radial drawings, HV-Drawings, Recursive winding), Drawings of planar graphs (Straight-line drawings, Orthogonal drawings, Visibility drawings); Survey of recent developments in computational geometry.

Course Code: CSE 6171
Credit Hour: 3.00
Prerequisite:

Fundamentals of Digital Image Processing; Image enhancement: Gray scale moods and histogram mod, Discrete transforms, Fourier transform, Discrete cosine transform, Walsh-Hadamard transform, Haar, PCT, filtering, wavelet transform, pseudo-color; Image enhancement: Sharpening and smoothing; Image restoration: System model, Noise, Noise removal, Degradation model, inverse filter, Freq. filters, geometric transforms; Image compression: System model, Lossless and Lossy methods; Medical image analysis: Human brain mapping, Volume visualization, Biomedical computing, arterial tree morphometry, spatial transformation models, image standardization, positron emission tomography images, voxel histograms, retrieval strategy, medical image archive, lossy compressed digital mammograms, tissue characterization, unsupervised segmentation, fifth generation systems, image re-sampling, anisotropic adaptive filtering, shell rendering, digital subtraction angiography, human perceptual features, etc.

Course Code: CSE 6113
Credit Hour: 3.00
Prerequisite:

Definition of Data Warehousing, Business Intelligence and Information Management; Technical techniques and concepts for Data Warehousing and Business Intelligence – EDW, dimensional modeling, OLAP etc; Introduction to the business requirements for Data Warehousing – such as Balanced Scorecard, Customer Relationship Management and Supply Chain Management; Discussion on Data Warehouse strategy and architecture – Enterprise Data Warehouse, Data Marts, Operational Data Store, Metadata Repository etc; Introduction to Metadata Management and Information Management; Platon Insight® – The Idea behind the structure and design; IM program perspective – scope for single projects; Contents of a BI-project–activities; Methodology implementation – meaning in daily life; Methodology impact on knowledge gathering, efficiency and added business value; Handling and use of documentation.

Course Code: CSE 6115
Credit Hour: 3.00
Prerequisite:

Financial algorithms used in applications of computer science in financial decision analysis, risk management, data mining and market analysis, and other modern business processes; 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; Algorithms for financial risk assessment and presents the security concepts and challenges of financial information systems.

Course Code: CSE 6143
Credit Hour: 3.00
Prerequisite:

Mobile operating systems and architectures; Application development languages, Development environments and simulators, Challenges in developing mobile applications compared to other applications; User interfaces, Location-based services, Storing and retrieving data principles of application design and development; Kernel programming, Input methods; Data handling; Database, Intents; Activities; Broadcast; Map-based activities using web-services e.g. Google; Network techniques e.g. Blue-tooth, Wi-Fi, GPS; localization and sensing; Application-neutral APIs to access hardware of mobile devices e.g. camera, phone, sensor hardware etc; object-based inter-process communication (IPC) between applications; Raster graphics engine.

Course Code: CSE 6145
Credit Hour: 3.00
Prerequisite:

Grid computing: definition of grid, infrastructure of hardware and software, applications, Grid architecture: overview of resource managers, overview of grid systems, Grid application management: Grid Application Description Languages, application partitioning, Meta-scheduling, mapping, monitoring, Web services, grid portals; Distributed computing: trends of distributed computing, evolution of Cloud computing; Cloud computing basics: properties and characteristics, different service models, deployment models; Infrastructure as a Service (IaaS): IaaS basics, resource virtualization, server, storage, network; Platform as a Service (PaaS): PaaS basics, Cloud platform and management, computation, storage; Software as a Service (SaaS): SaaS basics, Web services, Web 2.0, Web OS; Cloud issues and challenges: Cloud provider lock-in, security, trust model; Case studies: Google Cloud infrastructure, Amazon Web services, Elastic Cloud, Storage Services, Microsoft Cloud infrastructure.

Course Code: CSE 6147
Credit Hour: 3.00
Prerequisite:

Conventional Software Management; Evolution of Software Economics; Improving Software Economics; The principles of conventional software Engineering and modern software management; Life cycle phases; Artifacts of the process : The artifact sets, Management artifacts, Engineering artifacts, programmatic artifacts; Model based software architectures: A Management perspective and technical perspective. Work Flows of the process; Checkpoints of the process; Iterative Process Planning; Project Organizations and Responsibilities; Process Automation; Project Control and Process instrumentation: The seven core Metrics, Management indicators, quality indicators, life cycle expectations, pragmatic Software Metrics, Metrics automation; Future Software Project Management: Modern Project Profiles, Next generation Software economics, modern process transitions; Case Study: The command Center Processing and Display system- Replacement (CCPDS-R), COCOMO Cost Estimation Model – Change Metrics – CCPDS–R. Projects and Presentations using a state of the art tool.

Course Code: CSE 6151
Credit Hour: 3.00
Prerequisite:

Computer Game Software Design: Games creation, game-play, game concepts, design process, creative play, player motivation, environment and interface design, game-balancing, character design and design documentation; Computer Game Software Production: Creating and publishing electronic games, budgeting, team roles and responsibilities, group dynamics, design documentation, project management and evaluation, Game development in mobile phone platform.

Course Code: CSE 6153
Credit Hour: 3.00
Prerequisite:

Introduction; Molecular biology basics; Restriction mapping algorithm; Motif in DNA sequences, motif finding algorithms; Genome rearrangements; DNA sequence alignments; Gene prediction; Sequence alignment algorithms; DNA sequencing, Genome sequencing, Protein sequencing and Spectrum graphs; Combinatorial pattern matching: BLAST and FASTA; Clustering; Stochastic Models of Sequence and Genome Evolution; Phylogenies: Enumerating phylogenies, The probability of sequences related by a specified phylogeny, the minimal number of events needed to explain a data set (Parsimony); Likelihood and algorithms (Markov Chain Monte Carlo) for inference based on the likelihood; Software packages for sample-based inference; Alignment Algorithms; Network Inference and Network Evolution; Detection of Recombination in Sequences; Advanced topics related to Systems Biology and Synthetic Biology;

Course Code: CSE 6155
Credit Hour: 3.00
Prerequisite:

Enterprise architecture (EA): A detail study for EA using latest research and best practices including case studies, Methodologies on how to identify the right thing for the enterprise, an EA implementation methodology, assess risks and values for an enterprise architecture program, governance and organizational aspects of implementing an enterprise architecture program; Enterprise architecture frameworks: Three enterprise architecture frameworks: Zachman Enterprise Framework, Open Group Architecture Framework (TOGAF) and Enterprise Architecture Cube methodology; Enterprise Service Oriented Architecture (SOA): Realization of enterprise architecture, design and implementation; Unique aspects of enterprise architecture and development: Requirements engineering and software engineering methods for enterprise development

Course Code: CSE 6157
Credit Hour: 3.00
Prerequisite:

What is a Model; Foundations: Logic, Proof Techniques, Sets, Relations, Functions, Sequences & Induction; State Machines: State Machine 1&2, FSP, Reasoning about state Machines; Z: Introduction to Z, Z techniques, Z examples, SM Refinement and Abstraction, Z Refinement and Abstraction, Concurrency: Introduction to Concurrency, Concurrent State Machines, FSP 2- Modeling Techniques, Reasoning about Concurrency, Linear Temporal Logic, Linear Temporal Logic in FSP; Automated Reasoning 1, Formal Models in Practice: Automated Reasoning 2; FM in the Real World, Introduction to Petri nets, Reasoning about Petri Nets, UML.

Course Code: CSE 6159
Credit Hour: 3.00
Prerequisite:

Overview; Requirements Engineering Reference Model; Requirements Modeling; Requirements Elicitation; Software Requirements Specification (SRS) document; Requirements Writing: Informal Specification Notations, Formal Specification Notations, Specification of Non-behavioral Requirements; Requirements Validation; Cost Estimation.

Course Code: CSE 6163
Credit Hour: 3.00
Prerequisite:

Introduction to GIS, Principles of cartography, Projections, Sampling the world – errors, conversion, coordinate systems Generalization, The raster vs. vector debate, Cartographic modeling: Representations, Operations, Modeling; Database issues: Review of hierarchical, network, and relational models, Integration of spatial and non-spatial data, Object-oriented methods, Image databases; Review of existing geographic information systems, Spatial data structures, Representations of topology, Point databases, Line segment databases, Digital terrain models, Triangulated Irregular Networks (TINs), Triangulations methods, Spatial interpolation, Similarity Searching, neighbor finding, and distance-based indexing Spatial networks, Spatio-textual databases, GPU spatial algorithms, Cloud computing spatial algorithms.

Course Code: CSE 6165
Credit Hour: 3.00
Prerequisite:

Generally Accepted Auditing Standards (GAAS); Phases of an IT Audit: Establish the Terms of the Engagement, Preliminary Review, Establish Materiality and Assess Risks, Plan the Audit, Consider Internal Control, Perform Audit Procedures, Issue the Audit Report; Planning the Audit: Materiality, Risk Assessment: Documentation of Risk Assessment, The Audit Plan, Planning Memo; Evaluation of Internal Controls: General Controls, Application Controls, Tests of Controls; Audit Procedures: Audit Sampling: Selecting the Sample, Evaluation and Documentation of Samples, Computer Assisted Auditing Techniques (CAATs), Evidence; Completing the Audit: Reporting: Types of Auditors’ Opinions, Audit Documentation, Resources.

Course Code: CSE 6165
Credit Hour: 3.00
Prerequisite:

Generally Accepted Auditing Standards (GAAS); Phases of an IT Audit: Establish the Terms of the Engagement, Preliminary Review, Establish Materiality and Assess Risks, Plan the Audit, Consider Internal Control, Perform Audit Procedures, Issue the Audit Report; Planning the Audit: Materiality, Risk Assessment: Documentation of Risk Assessment, The Audit Plan, Planning Memo; Evaluation of Internal Controls: General Controls, Application Controls, Tests of Controls; Audit Procedures: Audit Sampling: Selecting the Sample, Evaluation and Documentation of Samples, Computer Assisted Auditing Techniques (CAATs), Evidence; Completing the Audit: Reporting: Types of Auditors’ Opinions, Audit Documentation, Resources.

Course Code: CSE 6237
Credit Hour: 3.00
Prerequisite:

Introduction; Role of a software architect; Software architecture design effort; UML; Functional semantics using OCL; S/W architecture: process, specification, measurement, evaluation; Components of a good software architecture; Appropriate Architectural Styles; Software Design Versus Software Architecture; Common Tools for Design Software Architecture; Mitigating changes within architecture; Object Oriented Design Techniques; Software Design Pattern; Design Review.

Course Code: CSE 6239
Credit Hour: 3.00
Prerequisite:

Brief introduction to software systems and SDLC: Basic Testing Vocabulary, Scope of Testing, Testing Constraints, Life Cycle Testing, Independent Testing, Levels of Testing, “V” Concept of Testing; Testing Techniques: Structural versus Functional Technique Categories, Verification versus Validation, Static versus Dynamic Testing, Examples of Specific Testing Techniques; Test Administration: Test Planning, Customization of the Test Process, Budgeting, Scheduling; Create the Test Plan: Prerequisites to test planning, Understand the Characteristics of the Software Being Developed, Build the Test Plan, Write the Test Plan; Test Case; Test Case Design; Building test cases; Test data mining; Test execution; Test reporting; Defect Management; Test Coverage – Traceability matrix; Test Tools used to Build Test Reports; Managing Change: Software Configuration Management, Change Management; Risk Analysis and Management with examples; User Acceptance testing; Automation Testing Basics: Basics of automation testing, Factors for choosing a particular tool, major functional testing tools, Test management and bug tracking tools.

Course Code: CSE 6235
Credit Hour: 3.00
Prerequisite:

Introduction; Essential topics of the variant requirements analysis phases; Problem analysis; Prototyping the Requirements; Trawling for Requirements; Scenarios; Writing the Requirements; Reviewing the Specification; Requirements Reusing; Requirements Quality Gateway and risk analysis; Requirements Specification Template for Requirement Specification document.

Course Code: CSE 6231
Credit Hour: 3.00
Prerequisite:

Introduction to ERP; Characteristics of ERP systems; The good, the bad and the ugly side of implementing ERP systems; Types of ERP solutions available today; Costs of the project and budgeting for your ERP system; Implementation phases and timeline; Business model of the ERP systems; IT infrastructure, on-premise and cloud solutions; Integration with other solutions.

Course Code: CSE 6211
Credit Hour: 3.00
Prerequisite:

Gradient descent and logistic regression; Probability, continuous and discrete distributions; maximum Likelihood; Neural Networks: cost functions, hypotheses and tasks; training data; maximum likelihood based cost, cross entropy, MSE cost; feed-forward networks; MLP, sigmoid units; neuroscience inspiration; Learning in neural networks: output vs hidden layers; linear vs nonlinear networks; Backpropagation: learning via gradient descent; recursive chain rule (backpropagation); if time: bias-variance tradeoff, regularization; output units: linear, softmax; hidden units: tanh; Deep learning strategies; SCC/TensorFlow overview; Convolutional neural networks; Deep Belief Nets: probabilistic methods; Recurrent neural networks; Other DNN variants; Neural Turing Machines; Unsupervised deep learning; Deep reinforcement learning.

(This course includes developing deep learning projects using state-of-the-art libraries in deep learning)

Course Code: CSE 6229
Credit Hour: 3.00
Prerequisite:

Introduction: Big Data, Cloud Computing, Scalability; Big Data Design: Polyglot systems; Schemaless databases; Key-value stores; Wide-column stores; Document-stores; Distributed Data Management: Transparency layers; Distributed file systems; File formats; Fragmentation; Replication and synchronization; Sharding; Consistent hash; LSM-Trees; In-memory Data Management: NUMA architectures; Columnar storage; Late reconstruction; Light-weight compression; Distributed Data Processing: Distributed Query Processing; Sequential access; Pipelining; Parallelism; Synchronization barriers; Multitenancy; MapReduce; Resilient Distributed Datasets; Spark; Stream management and processing: One-pass algorithms; Sliding window; Stream to relation operations; Micro-batching; Sampling; Filtering; Sketching; Big Data Architectures: Centralized and Distributed functional architectures of relational systems; Data Wareshousing architectures; Service Oriented Architecture; Lambda architecture

Course Code: CSE 6221
Credit Hour: 3.00
Prerequisite:

An Overview: Decision-Making Systems, Modeling, and Support; Business Intelligence: Data Warehousing, Data Acquisition, Data mining; Artificial Intelligence and Expert Systems: Knowledge-Based Systems; Knowledge-Based Decision Support and AI; Knowledge Acquisition, Representation and Reasoning; An Overview of Expert Systems; Expert System Development. Intelligent Systems over the Internet; Advanced Intelligent Systems; Collaborative Computing Technologies: Group Support Systems; Enterprise Information Systems. Electronic Commerce; Integration, Impacts, and the Future of Management-Support Systems.

Course Code: CSE 6225
Credit Hour: 3.00
Prerequisite:

Study on Customers and Markets in Business decision; gathering, analyzing, and interpreting data about markets and customers; market research for managers; marketing decision problems: target market selection, new product or service introduction, customer retention, pricing; Market Data Acquisition; Market Data analysis techniques using S/W; Machine Learning/Deep Learning based Market Prediction; identification of market pattern for managerial decision

(This course will include practical projects using Machine Leaning/Deep Learning)

Course Code: CSE 6213
Credit Hour: 3.00
Prerequisite:

Introduction: NLP tasks in syntax, semantics, and pragmatics; applications such as information extraction, question answering, and machine translation; the problem of ambiguity; the role of machine learning; N-gram Language Models: The role of language models; Simple N-gram models; Estimating parameters and smoothing; Evaluating language models; Part Of Speech Tagging and Sequence Labeling: Lexical syntax; Hidden Markov Models (Forward and Viterbi algorithms and EM training); Basic Neural Networks: perceptron; backpropagation; LSTM Recurrent Neural Networks: Understanding; Long and Short term memory; Syntactic parsing: Grammar formalisms and treebanks; Efficient parsing for context-free grammars (CFGs); Statistical parsing and probabilistic CFGs (PCFGs); Lexicalized PCFGs; Neural shift-reduce dependency parsing; Semantic Analysis: Lexical semantics and word-sense disambiguation; Compositional semantics; Semantic Role Labeling and Semantic Parsing; Information Extraction (IE): Named entity recognition and relation extraction; IE using sequence labeling; Machine Translation (MT): Basic issues in MT; Statistical translation; word alignment; phrase-based translation; synchronous grammars.

Course Code: CSE 6281
Credit Hour: 3.00
Prerequisite:

Technologies to deliver healthcare to the public: models for the delivery of consumer health information, Internet-based information delivery, access to patient information and privacy issues, quality of consumer health information, health literacy and health information literacy, design and development of consumer health information resources, consumer access to clinical information and current research.

Course Code: CSE 6283
Credit Hour: 3.00
Prerequisite:

Basic data management concepts and current biological database software tools: Biological data types and databases; Defining database schemas using relational model; Querying databases using SQL; Designing conceptual data models; Indexing and performance issues in biological databases; E-R data modeling, Data collection methods, data integration methods, Ontology standards, database-driven analytics; Clinical database; XML Database; Web Database; NoSQL database.

Course Code: CSE 6285
Credit Hour: 3.00
Prerequisite:

Human factors engineering, including its principles and subspecialties; Evaluation of a health informatics problem using human factors engineering concepts and methods; Critique scientific articles and other readings on human factors engineering; Synthesized knowledge from different areas of human factors engineering to solve a contemporary health informatics problem; Development and communication of a research study proposal to apply human factors engineering to a contemporary health informatics issue.

Course Code: CSE 6287
Credit Hour: 3.00
Prerequisite:

Introduction to Health Information Exchange; HIE Services Defined; The Five Stages of the HIE Organizational Life Cycle; Strategic and Business Plans to Create Sustainable HIE Models; Privacy, Security, Confidentiality, and Transparency; HIE Organizational Structures and Governance; Infrastructure, Architecture and Data Types; Identity and Location Resolution: Core Technologies for HIE; Standards and Interoperability; Measuring the Value of Health Information Exchange; Using HIE to Improve Population Health; Engaging Consumers Using HIE; Global Health Information Exchange; Future Directions for HIE.

Course Code: CSE 6289
Credit Hour: 3.00
Prerequisite:

Data munging and cleaning; sampling techniques; Genotype and Phenotypic Data; statistical methods, both parametric and non-parametric; Large Size Hospital Health Data; Apply different statistical packages on cleaning the large size data, evaluating different sampling concepts, generating the hypothesis, evaluating the features, and interpret the results for different hospital scenarios; Compare and contrast the domain specific knowledge of the large size insurance data for specific diseases and hospital care payment; Apply different statistical and correlation discovery packages for information extraction from the large size insurance data and interpret the results for the domain evaluation; Apply different statistical toolkits on the different integrated samples of Hospital (Phenotypic); Apply the analytical results to Precision Medicine; Apply different statistical methods for regression analysis over integrated genotypic and phenotypic data based on the sampling and domain specific knowledge; Introduction to survival analysis and application of different survival analysis concepts on phenotypic data for evaluating different disease specific treatment.

Course Code: CSE 6291
Credit Hour: 3.00
Prerequisite:

Design, implementation, and evaluation of electronic health record (EHR) system, Utilization of technology for data acquisition, storage, reuse, interoperability, exchange, and analysis. Evaluation of legal, ethical, and regulatory implications; Teams formation to manage implementation in healthcare organizations, analyze the design of existing EHR systems, Health Level 7 Reference Information Model (HL7 RIM), Continuity of Care Document (CCD), Gap analysis by Computerized Physician Order Entry (CPOE) systems; Picture Achieving and Communication System (PACS), DICOM (Digital Imaging and Communication in Medicine)

Course Code: CSE 6293
Credit Hour: 3.00
Prerequisite:

Introduction to HIT within Healthcare; Implementation of Decision Support System, bar code tracking, Electronic Health Records (EHRs), pay-for-performance incentives for e-prescribing; the Business of Healthcare – How the provider system makes money? – an analytical model; the Business of Healthcare – Micro and Macro Perspective; the Business of Healthcare – The role of HIT; Payment Models; Evaluating HIT financial performance – Micro and Macro perspective.

Course Code: CSE 6295
Credit Hour: 3.00
Prerequisite:

Evolution of public health systems in Bangladesh (ancient, colonial & post-independence), Health Planning in Bangladesh (Committees, Planning, National Health Policies), Public health systems in Bangladesh (Center, State, District & Village level), Rural development, corporate philosophy, Evolution and organization of private health systems in Bangladesh and Current trends in private healthcare in Bangladesh.

WHO- Objective, functions; UNICEF- objective and functions; Different Models of Healthcare: The Beveridge Model, The Bismarck Model, The National Health Insurance Model, The Out-of-Pocket Model; Brief Introduction of Health System of different countries: USA, UK, Canada, Australia, Sweden, and Germany.

Course Code: CSE 6297
Credit Hour: 3.00
Prerequisite:

Introduction to population studies, Issues of Bangladesh society & culture, Nuptiality & Fertility, Reproductive health, Population and Development: policies, programs & evaluation, introduction to epidemiology: concept, terms, aims & usage; definition of epidemic, endemic, pandemic, sporadic. Prevalence and Incidence. Epidemiological methods- basic idea of Cohort study, Case Control study and RCT. Epidemiology of communicable diseases: TB, STDs, Diarrhea, HIV/AIDS, etc.; Epidemiology of Non communicable diseases: CHD, Cancer, Diabetes, Hypertension & Obesity, etc.

Course Code: CSE 6309
Credit Hour: 3.00
Prerequisite:

Definition of Telehealth and mHealth; Core Aspects of Telehealth and mHealth: Health Visits, Electronic Health Record (ERH), Digital and mobile Apps; Telehealth, mHealth, Virtual Healthcare; Core Areas of Telehealth and mHealth Healthcare: Telehealth with synchronous and asynchronous aspect, Remote patient monitoring aspect; Digital Therapeutics; Care Navigation: Patient self-directed care with web and mobile app, Digital-triaging; Hybrid Healthcare; Virtual Healthcare Solution, Digital Prescriptions, Virtual Pharmacy, Chatbot Assistant, Healthcare Dashboards, Medical Scribe, Evaluation of telemedicine systems, Telehealth and mHealth in the Home, Telemedicine for health professionals, Telehealth in the Developing World, Human and sociotechnical factors of Telehealth and mHealth, Ethical and legal challenges of Telehealth and mHealth, Future Trends in Telemedicine, Practical Examples/Case Studies , Telemedicine Policy & Access Considerations, Primary Care Telemedicine Overview, Tele-Dermatology Overview, Tele-Therapy Overview, Tele-OB/GYN Overview, Teleneurology/Telestroke Overview, Telestroke Structure with Telestroke Exam, Tele-ICU Overview, Tele-Psych Overview, Diabetes Management Overview, Medical Weight Management Overview, Tele-Rehab Overview, AR and VR in Telehealth and mHealth, Healthcare Innovation and Entrepreneurship.

Course Code: CSE 6241
Credit Hour: 3.00
Prerequisite:

Introduction to Artificial Intelligence (AI); AI based search, AI based optimisation; AI reasoning; AI based planning; Probabilistic AI, AI based diagnosis; Machine learning; Intelligent agents (reinforcement learning, information-theoretic foundations); and bio-inspired computing (neural networks, and evolutionary algorithms); Advanced Systems: Hybrid Systems, Artificial Life, AI Buzzwords galore; Genetic Engineering; Ontological Engineering.

Course Code: CSE 6197
Credit Hour: 3.00
Prerequisite:

The Internet of Things: Definitions, implications, perspectives, and some stats, a simplified model, architecture, Industry Markets and Applications, Issues and Challenges, Planning a Deployment, Industry and academic trends, Business models and projected growth, Case Study and Examples; Internet: layers, protocols, packets, services, performance parameters of a packet network as well as applications such as web, Peer-to-peer, sensor networks, and multimedia; Local Area Networks; Mobile Networking; Real-time networking; Data Storage in Cloud.

Course Code: CSE 6305
Credit Hour: 3.00
Prerequisite:

Introduction of Wireless Body Area Network (WBAN); WBAN Architecture; WBAN Requirements and Workflow: Requirements for Wireless Medical Sensors in WBAN, Monitoring Sensors, Traffic Types, Work Flow; WBAN Standards and Technologies; WBAN Applications: Medical Applications, Remote Healthcare Monitoring, Assisted Living, Telemedicine, Non-Medical Applications: Sports, Military, Life Style and Entertainment, Energy Consumption, and Security and Safety in the WBAN.

Course Code: CSE 6299
Credit Hour: 3.00
Prerequisite:

Introduction to modern networking practices: different elements of modern networking, requirements and technology; Software-Defined Network (SDN): background and motivation, evolution of SDN, SDN data plane and OpenFlow; SDN control plane, SDN application plane; Case study of SDN: Data Centers; Network Function Virtualization (NFV): Virtualization, NFV concepts and architecture, NFV functionalities; NFV deployment in the cloud, relationship between SDN and NFV, Service Function Chaining; Case study of NFV: 5G communication.

Course Code: CSE 6301
Credit Hour: 3.00
Prerequisite:

Internet architecture, introduction to the current Internet, investigate its problems, evolutionary approach and revolutionary or clean slate approach for designing the future Internet, Internet testbeds, transition from IPv4 to IPv6, access network, naming and addressing for future Internet, content-centric networking, routing in future internet, manageability in future Internet, mobility and quality of service in future Internet, future Internet service and applications, recent topics such as artificial intelligence and fifth generation network, IoT-Cloud integration and research trends in future Internet.

Course Code: CSE 6303
Credit Hour: 3.00
Prerequisite:

Overview of systems programming; Users, files, and manuals; Directories, file properties and file systems; Terminal control and signals; Event driven programming; Process Management: process and programs, Threads and Concurrency, Spawn, Sleep, Wait, Synchronization; Memory Management/Memory Models; Device management: Device Drivers; Performance Measurement and optimization; System Calls; Inter-Process Communications: I/O redirection and pipes, Servers and Sockets, Shared Memory, Signals and signal handlers.

Course Code: CSE 6199
Credit Hour: 3.00
Prerequisite:

Introduction to Big Data: characteristics of Big Data and dimensions of scalability; Data Science: getting value out of Big Data, foundations for Big Data systems and programming, getting started with Hadoop; Big Data Modelling and Management Systems: Big Data modelling, Big Data management, designing a Big Data management system; Big Data Integration and Processing: retrieving Big Data, Big Data integration, processing Big Data, Big Data analytics using Spark; Machine Learning with Big Data: introduction to machine learning with Big Data, data exploration, classification, evaluation of machine learning models, regression, cluster analysis, and association analysis; Graph Analytics for Big Data: introduction to graphs, graph Analytics, graph analytics techniques, computing platforms for graph analytics;

(This course will include practical projects on developing big data projects using cloud platforms provided by Sparks, Google or other state-of-the-art frameworks)

Course Code: CSE 6179
Credit Hour: 3.00
Prerequisite:

Introduction to FORENSICS: Relationship between security, forensics and e-Discovery; Accounting Forensics, Computer Forensics, Journaling and it requirements, Standardized logging criteria, Journal risk and Control Matrix, Neural networks, Misuse detection and Novelty detection; Incident response procedure; Forensic investigation process; Acquisition of the different types of data; Computer forensic tools; how to handle evidence: chain of custody; How to perform forensic analysis; how to comply with legal and industry regulations; Sample case: conducting a forensic analysis; Malware forensics.

Course Code: CSE 6177
Credit Hour: 3.00
Prerequisite:

Introduction: Types and purpose of hacking, Network hacking, Web hacking, Password hacking; A study on various attacks: Input validation attacks, SQL injection attacks, Buffer overflow attacks, Privacy attacks; ATTACKS AND FIREWALLS: TCP / IP, Checksums, IP Spoofing, port scanning, DNS Spoofing; Dos attacks: SYN attacks, Smurf attacks, UDP flooding, DDOS Models; Firewalls: Packet filter firewalls, Packet Inspection firewalls Application Proxy Firewalls. THREATS: Fundamentals of Computer Fraud, Threat concepts, Framework for predicting inside attacks, Managing the threat, Strategic Planning Process; Architecture strategies for computer fraud Prevention, Protection of Web sites; PENETRATION TESTING: Intrusion detection system, NIDS, HIDS, Penetrating testing process, Reducing transaction risks, Key Fraud Indicator selection process customized taxonomies, Key fraud signature selection process.

(All the codes of Ethical Hacking will be implemented by HTML, JavaScript, SQL, PHP, Perl, C/C++, Ruby, Python, Java, LISP, and Assembly Language)

Course Code: CSE 6195
Credit Hour: 3.00
Prerequisite:

Cyber Security Standards Overview; Cyber Security Standards Characteristics; Cyber Security Standards Interaction; Cyber Security Standards Developers; International Standards Development Organizations; Regional Standards Development Organizations; National Standards Development Organizations; Consortia, Industry Alliances, and Associations; US Government Standards Developers; Getting Involved in Standards Development; List of Security Standards/Frameworks: ISO/IEC 27001/2, NIST 800- 53/CSF, CIS 20, ISACA COBIT 5, ISF, DISA, ITIL, PCI-DSS, OWASP, BSIMM, CSA 4.0.

Security monitoring: Passive Monitoring; Levels of Network Monitoring: Flow Data, Transaction Data, Alert Data, Packet Capture, Reassembly; Tools for packet capture, data flow, transaction and alert management; Network Security Monitoring Products; Bro, Wireshark, Sguil; Cyber Security Assessment: System lifecycle, System characteristics, Roles and Responsibilities, Assessment methodologies and Tools; Network Vulnerability Scanning; Log Review and Analysis: considerations, Tools, Sample log review and analysis tools; Cyber incident response and management: Phases of Cyber Attack; Duration and Cost of a cyber incident; Frameworks for incident response measures: ISO 27001, ISO 22301, PCI DSS; Incident response plans including: Policies, Procedures, Standards, Baselines, Guidelines; Responding to an event; Education and training; STOMP challenge; main challenges in incident response management.

Course Code: CSE 6187
Credit Hour: 3.00
Prerequisite:

Modern Network Security Threats: threats, mitigation techniques, and the basics of securing a network; Securing Network Devices: Secure administrative access to routers and switches; Authentication, Authorization and Accounting: AAA Authentication, Local and Server-based, Radious, TACACs+; Implementing Firewall Technologies: ACLs, Zone-based Firewalls; Implementing Intrusion Prevention; Securing the Local Area Network: implement endpoint and Layer 2 security features in devices; Implementing Secured Virtual Private Networks: VPN; Managing a Secure Network: create and implement a comprehensive security policy; Next generation firewalls.

Course Code: CSE 6243
Credit Hour: 3.00
Prerequisite:

Introduction to Vehicular Networks; Ad-hoc and Sensor Networks basics, Categories of Applications: Informative/Warning Systems(Traffic Information, Weather Warnings), Longitudinal Control (collision avoidance/warning, “look-through”obstructions to avoid accidents, platooning), Co-operative Assistance Systems(intersections, highway entrances); Intelligent transportation systems (ITS); Inter-vehicular communication (IVC); Mobile ad-hoc network (MANET); Vehicular ad-hoc network (VANET); Vehicle-to-vehicle (V2V) communication; Vehicle-to-infrastructure (V2I) communication; Network Issues; Security/Privacy Issues, Future Issues: Data Dissemination/Aggregation, Automatic Incident Detection, LISA(ODU’s approach), Evacuation Issues, Driver Distraction

Course Code: CSE 6245
Credit Hour: 3.00
Prerequisite:

Definition and related principles: Internet neutrality, Open Internet, Dumb pipe, End-to-end principle, Traffic shaping, Over-provisioning, Device neutrality; Issues: Discrimination by protocol, Discrimination by IP address, Favoring private networks, Peering discrimination, Favoring fast-loading websites; Legal aspects; Support: Control of data, Digital rights and freedoms, User intolerance for slow-loading sites, Competition and innovation, Preserving Internet standards, Preventing pseudo-services, End-to-end principle; Criticism: Reduction in investment, Significant and growing competition, investment, Deterring competition, Counterweight to server-side non-neutrality, Potentially increased taxes, Unnecessary regulations, Inability to make Internet accessible to the poor, Inability to allocate Internet traffic efficiently; Related issues: Data discrimination, Content caching, Quality of service (QoS), Wireless networks, Pricing models, Reactions to removing net neutrality in the US.

Course Code: CSE 6207
Credit Hour: 3.00
Prerequisite:

Introduction; Descriptive Statistics; Probability Distribution; Inferential Statistics; Regression and Analysis of Variance; Machine Learning: Differentiating algorithmic and model based frameworks, Regression : Ordinary Least Squares, Ridge Regression, Lasso Regression,

K Nearest Neighbours Regression & Classification; Supervised Learning with Regression and Classification techniques: Bias-Variance Dichotomy, Model Validation Approaches, Logistic Regression, Linear Discriminant Analysis, Quadratic Discriminant Analysis, Regression and Classification Trees, Support Vector Machines, Ensemble Methods: Random Forest, Neural Networks, Deep learning; Unsupervised Learning: Clustering, Associative Rule Mining; Challenges for Big Data Analytics; Data Creation: Designed experiments, Active Learning, Reinforcement Learning.

Introduction programing in to R/Python/Julia Programming or any other state-of-the-art language used for data science; Development environment for data science; Getting and cleaning data; Exploratory data analysis; Practical machine learning; Solving big data problems; Machine learning tools and techniques.

(In this course will include programming assignments focused on using machine learning algorithms using the prescribed language)

Course Code: CSE 6265
Credit Hour: 3.00
Prerequisite:

Definition; Dynamic and fluid area of digital health; Sociotechnical model for healthcare delivery and management; Connected Health in P’s medicine: Predictive Digital Technologies, Pre-emptive interconnected and intelligent solutions via mobile phone and Home-based devices, Personalized medicine, Participatory models with patient-centric information and experiences; PPPPPM: the “medicine of the future” for the new services and new economic and application models for both disease and healthcare; connected health services concentration: Sensing and Point of Care Devices, Communication Protocols and Technologies, Architectural Design and Applications and Interoperability, Security and Privacy, Business Added Value, Data Analytics; Connected Health from Disease care to Health care; Recent advances in the field of connected health systems, technologies, and services; Connected health for disease management and treatment. Precision and Preventive healthcare services at reduced cost; The future of Connected Health and digital age of medicine; Connected health informatics, systems, technologies, and services for better healthcare and well-being.

Course Code: CSE 6267
Credit Hour: 3.00
Prerequisite:

Health IT, Anatomy of medical practice, Ontologies, Interoperability, Hardness of interoperability, HIPAA, Models, Information Governance, Standards Development Organizations, Clinical Terminology, SNOMED CT, SNOMED CT Concept model, Implementing terminologies, HL7 v2, HL7 v3 RIM, Constrained information model, Clinical Document Architecture, HL7 dynamic modeling, Document sharing IHE XDS, Principles of FHIR, The FHIR RESTful API, FHIR Resources, Conformance and terminology, Implementing FHIR.

Course Code: CSE 6269
Credit Hour: 3.00
Prerequisite:

Introduction, outline and implement policies, guarantee communication and coordination between employees, automate routine tasks, design the patient-oriented workflows, advertise services, manage human and financial resources, provide the uninterrupted supply chain, implement data security, audit controls and policy compliance issues.

Course Code: CSE 6271
Credit Hour: 3.00
Prerequisite:

Introduction; role, values, and ethical obligations of the HIM Professional; ethical principles for decision making; professional values and obligations inherent in the Code of Ethics, including those important to patients, the healthcare team, employers, the public, peers and colleagues, and professional associations; steps in an ethical decision-making process; some of the core ethical problems health information management, including those related to the release of health information and coding.

Course Code: CSE 6209
Credit Hour: 3.00
Prerequisite:

Central Dogma of Molecular Biology; Modern genomics and the experimental tools; Next-generation sequencing: DNA, RNA, and epigenetic patterns; Galaxy project: Using Python; ChIP-Sequence Analysis with MACS; Algorithms for DNA sequencing, assembly; Command line tools; Tools from Bioconductor project: Using R; Statistics for Genomic data: clustering, dimensionality reduction, regression, inference; Working with Genomic data.

Course Code: CSE 6215
Credit Hour: 3.00
Prerequisite:

Introduction to Spatial Data Science; Importance issues: DBMS problems, topology, spatial indexing, and spatial big data; Spatial autocorrelation, map projection, uncertainty, and modifiable areal unit problem; Open source software: QGIS, PostgreSQL and PostGIS and Hadoop; Spatial Data Science Problems; Geographic Information System (GIS); Layers of GIS: spatial reference framework, spatial data model, spatial data acquisition systems, spatial data analysis, and geo-visualization; Steps of formulation of physical earth, geoid, ellipsoid, datum, and map projections; Coordinate transformation between different map projections; Spatial data acquisition systems; Spatial data analysis; Geovisualization and information delivery; Spatial DBMS; Spatial big data processing using Hadoop MapReduce; Spatial data analysis: Proximity and Accessibility, Spatial Autocorrelation, Spatial Interpolation, Spatial Categorization, Hotspot Analysis; Practical Applications of Spatial Data Science.

Course Code: CSE 6217
Credit Hour: 3.00
Prerequisite:

Introduction to E-Business Technologies: Overview of E-Business, Essential elements of B2C E-Commerce Websites, E-Commerce Models, Internet Marketing; Enabling Technologies for E-Commerce Applications: Electronic Payment Systems, Computer and Network Security, Internet Taxation; Web Servers; Building a Shopping Cart using S/W; Wireless Internet and Mobile Business; Collaborative E-Business Technologies: globally distributed teams, Virtual Teams

Course Code: CSE 6181
Credit Hour: 3.00
Prerequisite:

General computer security concepts: security policies, models and mechanisms related to confidentiality, integrity, authentication, identification; Communications security; Security assurance and Secure design principles; legal and ethical issues in security; Infrastructure security; Basics of cryptography (e.g., digital signatures); Network Security(e.g., intrusion detection and prevention); operational/organizational security; Risk Management; Standards and methodologies for security evaluation and certification.

Course Code: CSE 6183
Credit Hour: 3.00
Prerequisite:

Introduction to Steganography; Privacy; Transposition and Substitution Ciphers; Rotor Machine and Polyalphabetic Ciphers; Digital Signatures and Authentication; Public Key Systems; RSA System; Stream Ciphers; Pseudorandom generators; Steganography; Steganographic methods: Least significant bit substitution (LSB), Transform domain techniques, Cover generation methods, Random interval method, Pseudorandom permutations, Image downgrading, Cover regions and parity bits, Palette-based images, Digital Watermarking; Steganographic tools; Digital watermarking; Applications of digital watermarking: Broadcast monitoring, Owner identification, Transaction tracking, Content authentication, Scrambling attack, Synchronization attack, Copy attack, Ambiguity attack.

Course Code: CSE 6185
Credit Hour: 3.00
Prerequisite:

Setting the Stage: Defining threats to your Web assets, Surveying the legal landscape and privacy issues, Exploring common vulnerabilities; Establishing Security Fundamentals: Modeling Web security, Encrypting and hashing; Augmenting Web Server Security: Configuring security for HTTP services, Securing communication with SSL/TLS, Detecting unauthorized modification of content; Implementing Web Application Security: Employing OWASP resources, Securing database and application interaction, Managing session authentication, Controlling information leakage, Performing input validation; Enhancing Ajax Security: Ajax features, Assessing risks and evaluating threats; Securing XML Web Services: Diagnosing XML vulnerabilities, Protecting the SOAP message exchange; Scanning Applications for Weaknesses: Operating and configuring scanners, Detecting application flaws; Best Practices for Web Security: Adopting standards, Managing network security.

Course Code: CSE 6189
Credit Hour: 3.00
Prerequisite:

Introduction; Phone and Block Chain; Centralized Ledger; Distributed Ledger; Power of Distributed Ledger; Working Mechanism of Distributed Ledger; Introduction to Cryptography: Digital Signatures, Cryptographic Hash Functions; Cryptographic Data Structures: Hash Pointers, Append-Only Ledgers (Block Chains), Merkle Trees; Bitcoin’s Protocol: Keys as Identities, Simple Cryptocurrencies, Decentralization through Distributed Consensus, Incentives, Proof of Work (Mining); Bitcoin Blocks, Splitting and Sharing Keys, Proof of Reserve, Proof of Liabilities; Anonymity, Pseudonymity, Unlinkability; Cryptocurrency Technologies: Smart Property Efficient micro-payments.

Course Code: CSE
Credit Hour: 3.00
Prerequisite:

Cloud Computing Basics: Introduction to Cloud Computing, Definition, Characteristics, Components, Cloud provider, SAAS, PAAS, IAAS and Others, Organizational scenarios of clouds, Administering & Monitoring cloud services, benefits and limitations, Comparison among SAAS, PAAS, IAAS; Role of Grid in Implementing Cloud Computing: Basics of Grid Computing, Grid Architecture, Distributed computing in Grid and cloud, Interoperability in Grid and cloud, Modelling and Simulation of cloud and grids; Virtualization: Introduction to virtualization, concept and properties of virtualization, CPU virtualization, memory virtualization, I/O virtualization, Forms of CPU virtualization, Role of Virtualization in cloud computing, Hypervisors, Virtualization Security concerns; Cloud Security: Privacy and Security in cloud, Cloud Computing security architecture: Architectural Considerations, General Issues, Infra structure security at Network level, Host level and Application level, Security as a Cloud Service; Policy and Governance for Cloud Computing; Compliance and Legal Considerations; Disaster Recovery and Business Continuity Planning in the Cloud; Identity and Access Management (IAM); Data Security in the Cloud; Intrusion Detection and Incident Response; Risk, Audit, and Assessment for the Cloud.

Course Code: CSE 6193
Credit Hour: 3.00
Prerequisite:

Introduction to Cyber Crime: Concepts and Techniques, Categories and characteristics; Cyber Crime Methods: Stalking & Cyber Squatting, Cyber Extortion & Cyber Cheating, Cyber warfare & Cyber Terrorism, Phishing & Hacking; Internet Crime & Internet fraud; Computer Fraud Protection: Prevention Controls, Detection Controls, Mitigation Controls, Encryption / Decryption; Incident of Cyber crimes: Cyber Crime Reporting, Cyber Crime Investigation, Cyber Crime Management, Evidence Collection & Chain of Custody, Cyber Crime Risk Management, Cyber Forensics; Regulations and International standards; Privacy laws governing law enforcement, investigations in cyberspace; National Cyber Security Policy.

Course Code: CSE 6201
Credit Hour: 3.00
Prerequisite:

Introduction; Passive Monitoring; Levels of Network Monitoring: Flow Data, Transaction Data, Alert Data, Packet Capture, Reassembly; Flow Data Management Tools; Transaction Data Management Tools; Alert Tools; Alert Management Tools; Packet Capture Tools; Packet Capture Purpose, Stream Capture; Bro Capture; Monitoring Stack; Difference between NSM and IDS; Device Management; Security Event Management; Network-based Forensics; Intrusion Prevention; Deployment Consideration: Assets, Zones, Attackers; Data Collection and Alert Data; Network Security Monitoring Products; Sguil.

Course Code: CSE 6203
Credit Hour: 3.00
Prerequisite:

Cyber Security Assessment: System lifecycle, System characteristics, Roles and Responsibilities, Assessment methodologies and Tools; Network Scanning: Considerations, Tools; Vulnerability Scanning: Policy and Procedure vulnerabilities, Platform vulnerabilities, Network vulnerabilities, considerations, Tools, Sample vulnerability scanning tools; Password Cracking: considerations, Tools, Sample password cracking tools; Log Review and Analysis: : considerations, Tools, Sample log review and analysis tools; File Integrity Checking: considerations, Tools, Sample file integrity checking tools; Malware Detection: considerations, Tools, Sample malware detection tools; War Dialing: considerations, Tools, Sample war dialing tools; Wireless Testing: considerations, Tools, Sample wireless testing tools; Pentration Testing: considerations, Tools, Sample penetration testing tools

Course Code: CSE 6205
Credit Hour: 3.00
Prerequisite:

Security Fundamentals, Firewalls, Types of Firewalls, Overview of NextGen Firewall, Limitations of firewall, Intrusion Detection And Prevention, Intrusion risks, Security policy, Monitoring and reporting of traffics, Traffic shaping. Investigating and verifying detected intrusions, Recovering from, reporting and documenting intrusions, Define the Types of intrusion Prevention Systems.Intrusion prevention system basics, Limitations of Intrusion Prevention System.Spoofing Detection &Prevention, DDos & Dos mitigation techniques, Qos Policy.Introduction of Web Application Firewall, Packet Signature and Analysis, Virtual Private Networks, Deploy and managing VPN, VPN Performance tuning and error handling, DMZ and virtual host, Introduction of Reverse proxy and policies.

Course Code: CSE 6219
Credit Hour: 3.00
Prerequisite:

Introduction to Business Analytics; Predictive Analytics: lending analytics, financial analytics; Prescriptive Analytics: retail analytics, sales-force analytics, fortpolio analytics; Supply Chain analytics and Decision Support System; Linear Regression; Time Series Analysis; Data Mining: Cluster Analysis, Market Basket Analysis; Spreadsheet Models; Linear Optimization: Integer Linear Optimization, Nonlinear Optimization; Monte Carlo Simulation; Decision Analysis; Supervised Learning

Course Code: CSE 6223
Credit Hour: 3.00
Prerequisite:

Introduction to Expert System in Business; Basics of Spreadsheet Models; Optimization Tools of Spreadsheet Models; Artificial Intelligence Techniques: Overview of Genetic Algorithms; Decision Calculus Models: Fundamentals; Expert Systems Fundamentals; Demand Assessment & Forecasting Models; Expert Systems Applications; Genetic Algorithms for Product Design; Artificial Intelligence for Market Segmentation; Genetic Algorithms for Market Segmentation; Genetic Algorithms Applications; Product & Price Models; Advertising, Sales Promotion Models; Marketing Strategy Models.

Course Code: CSE 6227
Credit Hour: 3.00
Prerequisite:

Introduction to MIS; Organisations and Computing: IT-enabled Knowledge based Organisation, Internet and Web Services, AI in Organization; MIS in organization: technology roadmap for organization, Security Assurance, Managing Internet, IT interaction model, Challenges for managers; Data and Information: measuring data and information, information in organisational functions, types of information systems; Decision making and communication: Tactical decision, operational decision, strategic decision, decision with communication technology; Competing with IT: Bargaining Buyers-Suppliers, IT-based low cost competition; IT Strategy: information systems and competitive strategy- Value chain, the Role of CIO in planning, coordination, technology update, investment on technology; Business Process Integration with IT: Business processes, Enterprise Systems, Enterprise Resource Planning systems; SCM, CRAM and International Systems: Supply Chain Management Systems, Customer Relationships Management Systems, Challenges of Enterprise Systems Implementations, International Information Systems-Outsourcing and off-shoring; Decision Support System; E-Commerce; Managing Data Resources; Managing Social Media; Manging IT functions

Course Code: CSE 6233
Credit Hour: 3.00
Prerequisite:

Introduction to HRM; Careers in IT; Trends in IT Human Resources and its Determinants; Current perspective of IT HR; Future perspective of IT HR; Hiring IT professionals; Historical perspective of IT HR; Impact of IT outsourcing; IT professional associations; Morals, ethics, and social considerations; Preparing IT professionals (skills & competencies); Retaining IT professionals; Building IT Capacity for Leadership in a New Age; Building Great Talent and Effective Teams.

Course Code: CSE 6247
Credit Hour: 3.00
Prerequisite:

Introduction to Quantum Computing; Information and Computations; Characteristics of Computational Systems; Computability and Algorithms; Computational Complexity; The Multiverse Interpretation of Quantum Mechanics; Qubit; Qubit Measurement; Qubit Measurement; Systems with Multiple Qubits; Measuring the Multiple Qubits Systems; Quantum System Evolution and Computations; Deutsch’s Problem; Quantum Computer Prototype; Quantum Computer Prototype and Solving the Deutsch’s Problem; Factoring and the RSA; Factoring and Period Finding; Quantum Fourier Transform; Shor’s Algorithm.

Course Code: CSE 6249
Credit Hour: 3.00
Prerequisite:

An introduction to robotics from a cybernetic perspective; Overview of different types of robots and their application; History of robotics; Introduction to the robot simulations; Problem solving: commanding a mobile robot to move; A description of the components of a robot – sensors, actuators, ’brain’ and power supply; An understanding of different sensors, their operation and application; A description of motors; other robotic actuators; Problem solving: commanding a robot to achieve tasks on the basis of sensor information; Feedback for control and human-machine interaction; Feedback control of steering and speed in robots; Simple mathematical modeling of robots; Different forms of control strategies; Human-Computer Interaction: feedback, including haptics; Problem solving: commanding a robot to follow a path; Feedback for Learning and robot: robot interaction; An appreciation of neuron based brains through Braitenburg vehicles; Robot learning by trial and error; Multiple robots and artificial life, relating to biological processes; Problem solving: commanding a robot to traverse a maze.

Course Code: CSE 6251
Credit Hour: 3.00
Prerequisite:

General knowledge on Virtual Reality and Augmented Reality; Project management tools and techniques while working on VR and AR immersive projects; Development of 2D and 3D visual assets; Modeling, Texturing, Rigging and Animation of the assets for VR and AR applications; Interactive application development basic and advance; Scripting and programming techniques within interactive application development; Development and deployment of the VR applications for immersive systems; Creation mobile 3D applications with VR and AR functionality; Publishing applications for Android, iOS and for EON Studio based educational platforms.

Course Code: CSE 6253
Credit Hour: 3.00
Prerequisite:

History and Foundations of HCI; Research Frameworks in HCI; Modeling Social and Emotional Processes; Computer-Mediated Communication; Social and Embodied Interfaces I; Social and Embodied Interfaces II; Computer-Supported Collaborative Work; Speech Interfaces; Games; Crowdsourcing; Information Visualization; Ubiquitous Computing; Assistive and Accessible Interfaces; Future of HCI.

Course Code: CSE 6255
Credit Hour: 3.00
Prerequisite:

Introduction to Biomedical Engineering and Careers in Biomedical Engineering; Human Biology: Chemical basis of life, Brief introduction to Human anatomy and physiology; Biomechanics: Introduction to Biomechanics: Force, Moments and Couples system; Musculo-Skeletal systems, Structures: Methods of Joints; Bio-materials and it interaction with tissue; Introduction to present-day medical measurements and relevant imaging and non-imaging instruments; Biosensors: sensors for monitoring patients, Non-invasive biosensors for measuring metabolism and biophysical transport; The molecular biology and genetics starting with the chemistry and interactions of the key molecules of life: DNA, RNA, and protein; Computational biology: Algorithms for Biomedical/clinical data analysis for diagnostic, predictive, or prognostic purposes.

Course Code: CSE 6307
Credit Hour: 3.00
Prerequisite:

Human computer interface and systems design; healthcare decision support and clinical guidelines; system selection; organizational issues in system integration; project management for information technology change; system evaluation; regulatory policies; impact of the Internet; economic impacts of e-health; distributed health care information technologies and future trends.

Definition of HIS, Well-functioning HIS, Developing resilient and sustainable health systems, data collection, data store, data manage, processing, reporting, generation of quality data, Data to support key populations, health information systems & monitoring and evaluation, patient’s electronic medical record (EMR), hospital’s operational management, system supporting healthcare policy decisions, UN Sustainable Development Goals in Health.

Course Code: CSE 6257
Credit Hour: 3.00
Prerequisite:

Intro and overview of Neurocomputing; Philosophical Foundations & Historical Background; Individual Neurons; Membrane potentials and spikes; Simplified neurons and population nodes; Synaptic plasticity; Activation Dynamics & Information Processing; Bidirectional Excitation & Inhibition; Random networks; Feedforward networks; Competitive networks; Modular models; Hierarchical models. Different Learning: Reinforcement Learning, Hebbian Learning, Error Correction Learning; Large-Scale Functional Brain Organization.

Course Code: CSE 6167
Credit Hour: 3.00
Prerequisite:

Any expert proposed by the department and approved by syllabus committee will conduct this course. A subtitle and content shall be determined and approved by the same committee. In the transcript of the students the subtitle will follow the main title (Example: CSE 6167 Special Topic –I: Big Data).

Course Code: CSE 6169
Credit Hour: 3.00
Prerequisite:

Any expert proposed by the department and approved by syllabus committee will conduct this course. A subtitle and content shall be determined and approved by the same committee. In the transcript of the students the subtitle will follow the main title (Example: CSE 6169 Special Topic – II: Data Privacy).

Follow Us