May 11, 2024

OHIO University Graduate Catalog 2021-22

OHIO University Graduate Catalog 2021-22 [Archived Catalog]

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	CS 5440 - Data Communications In-depth coverage of computer-to-computer and program-to-program communication over modern computer networks focusing on the TCP/IP protocol family. Review of data communication issues, physical address binding, bridging, Ethernet, and Token Ring. Internetwork protocols, routing, domains, networks, and subnetworks. Transport protocols, reliability, flow control, retransmission, and acknowledgement. Distributed systems, server and client issues including verification, and authentication. High-level protocols and applications including electronic mail, network news, remote terminal interaction, and the World Wide Web. Requisites: Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will develop the ability to design data structures and algorithms to efficiently analyze, correlate, and search a large number of network packets to group them into various levels of granularity. Students will develop the ability to design experiments concerning the TCP protocol and congestion control algorithms and to analyze and interpret the resulting data. Students will develop the ability to design experiments concerning the TCP protocol and congestion control algorithms and to analyze and interpret the resulting data. Students will gain a basic understanding of other internet technologies and the ability to compare and contrast with IP. Students will gain a conceptual understanding of grouping physical networks to build virtual networks. Students will gain a conceptual understanding of the reasons that we use distributed systems. Students will gain a detailed understanding of Ethernet. Students will gain a detailed understanding of IPv4 addresses, subnet masks, and addressing notations. Students will gain a detailed understanding of RIP. Students will gain a detailed understanding of WWW protocols. Students will gain a detailed understanding of a particular remote procedure system. Students will gain a detailed understanding of all of the elements of the IPv6 Internet protocol. Students will gain a detailed understanding of electronic mail. Students will gain a detailed understanding of hardware addresses. Students will gain a detailed understanding of the FTP protocol. Students will gain a detailed understanding of the TCP protocol. Students will gain a detailed understanding of the causes of packet un-reliability. Students will gain a detailed understanding of the concept of a routing table and how it is used. Students will gain a detailed understanding of the mechanics of the UDP protocol. Students will gain a detailed understanding of the mechanisms used to provide realiability over an unreliable infrastructure. Students will gain a detailed understanding of the post-based addressing model. Students will gain a detailed understanding of the problems introduced by distributed systems. Students will gain a general understanding of OSPF, BGP, hello, and others. Students will gain a general understanding of TELNET/RSH/SSH. Students will gain a general understanding of congestion control. Students will gain a general understanding of sliding-window protocols. Students will gain a thorough appreciation for the security implications of using the Internet unsafely. Students will gain an understanding of CSMA/CD details.
	CS 5500 - Advanced Object Oriented Design and GUI Techniques Object-oriented design, interface design, and GUI development techniques; data structure usage and concepts; model-view-controller paradigm; input output and text parsing; exception handling; JAVA language syntax; large application development. Requisites: Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will develop the ability to create a large Java application. Students will develop the ability to design GUIs. Students will develop the ability to select proper data structures for various purposes. Students will gain a thorough understanding of object oriented design techniques, including object design, class libraries, interface design, polymorphism. Students will gain an understanding of the Java language with an emphasis on the differences with C++
	CS 5560 - Software Design and Development I All major phases of the software engineering lifecycle, including system engineering, requirements analysis, design, implementation and testing. Communication skills relevant to working in software engineering teams and interacting with customers. Teams of students perform all software engineering phases in response to the needs of a customer.mer. Requisites: Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will be able to explain all aspects of the software development cycle. Students will be able to produce a software requirement specification document. Students will be able to design and implement a solution to a complex software engineering project based on the specified requirements. Students will be able to perform using an effective team problem solving process. Students will be able to create a formal presentation and present it in front of an audience. Students will be able to perform software testing. Students will be able to discuss privacy issues, security issues, and ACM/IEEE software engineering code of ethics.
	CS 5580 - Operating Systems II Detailed discussion of virtual memory and backing stores. File system interfaces, implementation, and protection mechanisms. Process scheduling issues, policies, and mechanisms. Interprocess communication between programs on different computers. Distributed systems issues, examples, and implementation. Requisites: Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will develop the ability to design and implement a file system in user space Students will develop the ability to design and implement a simulation system to evaluate the performance of different memory management strategies Students will develop the ability to design and implement dynamic memory allocation library functions. Students will gain a detailed understanding of frame allocation Students will gain a detailed understanding of paging and swapping Students will gain a detailed understanding of segmentation Students will gain a detailed understanding of various page relacement algorithms Students will gain a general understanding of file access methods. Students will gain a general understanding of methods for allocating disk space. Students will gain a general understanding of the NFS file system Students will gain a general understanding of the UNIX fast file system Students will gain a general understanding of the Windows file system Students will gain a general understanding of the advantages, disadvantages, and tradeoffs of distributed file systems Students will gain a general understanding of the virtual file system (VFS) concept Students will gain a general understanding of various file system concepts: the file, mounting, ownership, permissions Students will gain a thorough understanding of a particular distributed file system Students will gain a thorough understanding of one particular file system Students will gain a thorough understanding of the principle of virtual memory Students will gain an understanding of the implications of the security features in memory management and file system implementations
	CS 5610D - Data Structures Various data structures, algorithms associated with data structures, and analysis of algorithms are explored. Topics include analysis of algorithms, dynamic arrays, tree structures, heaps, balanced trees, dictionaries, graphs and graph algorithms, and the complexity of sorting. Graph algorithms for depth first and breadth first search, shortest path, minimum cost spanning trees, and others are covered. Coverage of built in data structures and algorithms in modern programming languages included. Requisites: Credit Hours: 4 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture, 1.0 recitation Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will develop the ability to analyze simple iterative and recursive functions. Students will develop the ability to solve simple summations and recurrence relations. Students will develop the ability to use graphs and graph algorithms in programs to solve practical problems. Students will develop the ability to use tree traversal techniques for practical applications (e.g., evaluating expressions). Students will gain an understanding and ability to use the basic terminology concerning asymptotic analysis. Students will gain an understanding of basic graph algorithms for searching (breadth first, depth first), finding shortest paths (Dijkstra’s algorithm and Bellman-Ford), and finding minimum cost spanning trees (Kruskal’s and Prim’s algorithm). Students will gain an understanding of the average and worst case analysis of the standard sorting techniques. Students will gain an understanding of the basic data structures and algorithms associated with hash tables and their asymptotic running times. Students will gain an understanding of the basic data structures and operations on heaps and their implementations. Students will gain an understanding of the basic data structures for storing trees (arrays, linked data structures, left-child/right sibling approaches). Students will gain an understanding of the basic graph data structures and terminology. Students will gain an understanding of the basic operations on binary search trees and their asymptotic running times. Students will gain an understanding of the basic operations on graphs and their running times. Students will gain an understanding of the basic tree traversal techniques (pre, post, and inorder traversals) and their asymptotic running times.
	CS 5620 - Database Systems Introduces fundamental concepts in data modeling and relational database systems. Begins with entity-relationship (ER) modeling technique as a tool for conceptual database design. Relational data model and relational algebra are introduced next, followed by the SQL query language for relational databases. Functional dependencies, normalization, and relational database design algorithms are then discussed. Requisites: Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will be able to design and implement a database based on models. Students will be able to design an entity-relationship diagram to model an enterprise. Students will be able to use SQL in a host programming language to implement transactions against a database. Students will be able to express a database query as a relational algebra expression. Students will be able to express an interactive database query in SQL.
	CS 5750 - Internet Engineering Understanding internet protocols; network cabling, hubs, and switches; configuring network routers; configuring Unix and Windows workstations; measuring and analyzing network performance; and troubleshooting. Requisites: WARNING: No credit for both this course and the following (always deduct credit for first course taken): ITS 5750 Credit Hours: 4 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture, 3.0 laboratory Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will become comfortable with a large suit of debugging tools. Students will become comfortable with physical networking equipment. Students will become comfortable with various hardware and software debugging and analysis tools. Students will become fluent in configuring operating systems (Windows, Linux, OSX), bridges, and routers. Students will become fluent with the limitations and consequences of network firewalls. Students will develop expertise in carefully handling and connecting delicate networking equipment. Students will develop expertise in tracking down and solving networking problems. Students will develop the ability to apply the scientific principles for designing an experiment, predicting the outcome, and verifying the results. Students will develop the ability to quickly track down network problems, determine the cause, and correct the situation. Students will develop the ability to quickly, efficiently, and correctly set up a very complicated network of computers, switch gear, and wiring. Students will gain a thorough understanding of the ethics of network monitoring, email filtering, and packet analysis. Students will gain a thorough understanding of the relationship between network speed and congestion, and data throughput.
	CS 5800 - Artificial Intelligence This course covers the fundamental underpinnings of Artificial Intelligence (AI), including knowledge representation and search. It introduces AI applications and the AI programming languages, LISP and Prolog. Potential societal benefits and detriments of AI technology are discussed. Requisites: Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will be able to apply AI theory and techniques to build intelligent systems Students be able to express real-world relationships in first order predicate calculus. Students will be able to identify potential societal benefits and detriments of AI technology.
	CS 5830 - Machine Learning This course covers classification, regression and clustering algorithms, as well as introductory concepts in reinforcement learning. Topics include perceptrons, logistic regression, linear regression, Naive Bayes, nearest neighbors, Support Vector Machines, and Q-learning. The description of the formal properties of the algorithms are supplemented with motivating applications in a wide range of areas including natural language processing, computer vision, bioinformatics, and music analysis. Requisites: Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will be able to implement simple learning algorithms such as kernel perceptrons, ridge regression, nearest neighbors, or Q-learning. Students will be able to use gradient descent to solve optimization problems. Students will be able to implement and evaluate stochastic gradient descent. Students will be able to explain the importance of regularization in machine learning. Students will be able to create feature vector representations appropriate for a given problem. Students will be able to indicate what machine learning algorithm is appropriate for a given problem. Students will be able to use standard techniques such as k-fold cross-validation to conduct rigorous experimental evaluations. Students will be able to use third-party machine learning packages. Students will be able to solve optimization problems using Lagrange multipliers. Students will be able to explain temporal difference learning as gradient descent.
	CS 5900 - Special Topics in Computer Science Special project in one of various subfields of computer science or application area studied, investigated, and/or solved by individual student or small group working in close relationship with instructor. Suitable problems might include construction of compiler for a special purpose language, perfection of software to solve some significant problem, or the study of coherent subfield of computer science. May be repeated for credit. Requisites: Credit Hours: 1 - 4 Repeat/Retake Information: May be repeated for a maximum of 8.0 hours. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will be able to meet the outcomes of the course as established by the instructor.
	CS 6040 - Advanced Algorithms Advanced topics in the design and analysis of algorithms are explored. These topics include matching and network flow algorithms, randomized algorithms, and parallel algorithms, the theory of NP-completeness, NP-hard optimization problems, polynomial-time approximation algorithms, approximation schemes, approximability and non-approximability results. Requisites: CS 5040 or 5060 Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will be able to apply the theory of matchings to specific problems. Students will be able to apply the theory of network flow to specific computational problems. Students will gain an understanding of approximation complexity. Students will gain an understanding of bipartite and general matchings and associate algorithms. Students will gain an understanding of non-approximability results. Students will gain an understanding of polynomial-time approximation algorithms and schemes. Students will gain the ability to build approximation algorithms for NP-complete problems. Students will understand how to develop and analyze parallel algorithms. Students will understand how to develop and analyze randomized algorithms.
	CS 6050 - Parallel Computation Theory Topics in the theory of parallel computation are explored. Topics include the PRAM model, the Boolean circuit model, uniform circuit families, parallel complexity classes, reducibility, P-completeness, and the approximation of P-complete problems. Requisites: CS 5040 or 5060 Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will be able to describe complexity classes associated with parallel and circuit models. Students will be able to analyze parallel algorithms for various parallel computing models. Students will be able to describe parallel models of computation. Students will be able to construct a proof of P-completeness. Students will be able to describe P-completeness. Students will be able to construct parallel algorithms for various parallel computing models.
	CS 6060 - Computational Complexity Complexity of computational problems explored with respect to a variety of complexity measures. Topics iinclude deterministic time complexity, nondeterministic time complexity, the polynomial-time hierarchy, average-case time complexity, space-bounded complexity, circuit complexity, reductions, relativizations, and parallel models of computation. Requisites: CS 5060 Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will be able to place problems within their appropriate complexity classes. Students will gain an understanding of structural complexity, well-known complexity classes, and reduction techniques. Students will gain an understanding of the known relationships among complexity classes. Students will understand and be able to employ proof techniques related to computational complexity. Students will understand oralcle relativization results and their implications in structural complexity.
	CS 6120 - Real Time Systems Discusses real-time systems and their design principles. Studies the particular characteristics of these systems and some real-time programming technologies. Requisites: Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will be familiarized with a common reference model of real-time systems. Students will gain an understanding of dealing with resources and resource access protocols in real-time systems. Students will gain an understanding of design principles for applications with a mix of non real time, soft real time, and hard real time activities. Students will gain an understanding of design principles for applications with a mix of periodic, aperiodic and sporadic activities. Students will gain an understanding of different traditional real-time scheduling approaches. Students will gain an understanding of real-time extensions to general purpose operating systems. Students will gain an understanding of real-time operating system design principles. Students will gain an understanding of the characterization of real-time systems. Students will gain the ability to develop real-time applications with a wide range of real-time constraints.
	CS 6150 - Computational Genomics Prepares students to perform research in the field of bioinformatics. Reviews computer science research literature that pertains to bioinformatics to assist in the discovery of important unsolved bioinformatics problems that require basic research in computer science. Examines the research processes that are used in the field of bioinformatics. Writing-intensive course, requiring learning how to write, evaluate and review scholarly articles. Requisites: Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 seminar Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will be prepared to perform thesis research that will advance and/or employ state-of-the-art bioinformatics methods. Students will become familiar with the current computer science research literature that addresses topics in bioinformatics. Students will discover important unsolved bioinformatics problems that require basic research in computer science. Students will learn about the research processes that are used in the field of bioinformatics. Students will learn how to write, evaluate and review scholarly articles in the field of bioinformatics.
	CS 6250 - Computer Graphics and Visualization Comprehensive study of the principles of computer graphics and visualization. Course topics include geometric transformations, representing shape, lighting properties, data representation, and visualization algorithms. Projects involve designing programs to visualize complex data in 2,3 and higher dimensions. Requisites: Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will be able to design programs that use an appropriate shape representation for a given task. Students will be able to design programs that use basic computer graphics (2D objects). Students will be able to use lighting properties to enhance visualizations. Students will be able to design programs to visualize complex data in 2, 3, and higher dimensions. Students will be able to analyze and design visualizations that utilize the mathematical foundations of geometric transformations.
	CS 6410 - Medical Image Analysis Fundamentals of medical image processing and analysis. Image data acquisition from CT, MR, PET, SPECT, and ultrasound devices. Image segmentation, registration, and visualization. Requisites: Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will demonstrate knowledge of fundamental medical image analysis algorithms such as registration, segmentation, and visualization.
	CS 6420 - Artificial Intelligence in Medicine Artificial intelligence (AI) approaches for medical decision making and clinical support, including knowledge-based systems, Bayesian reasoning, and data mining. Medical applications of AI, including diagnosis, therapy selection, patient monitoring and patient education. Requisites: Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will be aware of the current literature and online resources and learn the state-of-the-art in medical Artificial Intelligence research and practice. Students will be prepared to conduct independent research in Artificial Intelligence in Medicine. Students will gain an understanding of the ethical, legal, social and other non-technical aspects of applying Artificial Intelligence in medical domains. Students will learn advanced Artificial Intelligence approaches that are especially well-suited to medical decision making and clinical support.
	CS 6440 - Advanced Topics in Computer Networking High-speed networking, experimental protocols, congestion control, reliability, security, distributed systems. Requisites: CS 5440 Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will end the course with a much better understanding of open research and development efforts in the networking field. Students will gain confidence in leading a class discussion and being the knowledge expert for assigned topics. Students will improve their ability to work on open ended programming and configuration tasks either independently or in small groups with only minimal instructions. Students will learn a healthy skepticism when reviewing the work of others. Students will learn a set of appropriate tools for analyzing network protocols and their network performance. Students will learn to form independent opinions based on readings and analysis of the research of others and will learn to vigorously defend those opinions during spirited debate. Students will learn to implement applications and protocols based on written specifications. Students will learn to thoroughly read published papers, follow references, and digest and retain the information.
	CS 6571 - Software Specification How software specifications are expressed and used. Emphasis on formal specifications and use of formal specifications in software verification and validation. Important formal specification models, including algebraic and axiomatic models, state/transition-based models, and temporal logic models, along with their related analysis techniques explored. Requisites: CS 5560 Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will gain knowledge of current research topics related to software specifications, e.g., model checking.
	CS 6572 - Software Design Advanced object oriented modeling studied. Teaches how to employ the Unified Modeling Language (UML) for advanced structural modeling, advanced behavioral modeling, and architectural modeling of software systems. Advanced structural modeling involves software components and their relationships. Concepts taught in advanced behavioral modeling pertain to hierarchical representations of external environment dependencies and interactions as well as concurrency. Also covers architectural modeling, including design patterns, collaborations, and deployment diagrams. Requisites: CS 6571 Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will demonstrate a graduate level understanding of current research topics in software design.
	CS 6573 - Software Implementation Provides the skills necessary for successful management of software engineering projects. Examines technical management techniques as well as interpersonal communication concepts. Principles taught applied to a software engineering program. Requisites: CS 6571 Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will demonstrate knowledge of how to manage a software engineering project implementation.
	CS 6800 - Advanced Topics in Artificial Intelligence Advanced topics in artificial intelligence (AI) studied. Concepts of heuristic search and knowledge representation studied in detail to provide a firm grounding in AI. Then an advanced topic studied, such as machine learning, natural language understanding, computer vision, and/or reasoning under uncertainty. Emphasis is to illustrate that representation and search are fundamental issues in all aspects of artificial intelligence. Requisites: Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will be able to apply heuristic search techniques to novel situations, including problems that are known to be intractable. Students will be able to apply predicate calculus techniques to build systems that can automatically prove theorems and reason. Students will be able to apply game theory to two person perfect information games. Students will be able to construct basic planning systems. Students will be able to analyze search algorithms and be able to apply them to AI problems.
	CS 6820 - Artificial Intelligence: Case-Based Reasoning Case-based reasoning (CBR) is an artificial intelligence (AI) paradigm, in which new problems are solved by reusing the solutions to previously encountered problems. Enables students familiar with AI problem solving techniques to explore CBR in depth. Featured will be: overview of fundamentals; discussion of research projects; CBR system implementation: and student presentations. Requisites: CS 5800 Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will become better prepared to conduct independent research in Case-Based Reasoning. Students will design and implement a prototypical Case-Based Reasoning system to perform a knowledge-based task. Students will explore the current literature and online resources to learn the state-of-the-art in Case-Based Reasoning research and application development. Students will learn the Case-Based Reasoning approach, in which intelligent systems solve problems by reusing the solutions to previously encountered problems.
	CS 6830 - Machine Learning Machine Learning is concerned with the design and analysis of algorithms that enable computers to automatically find patterns in the data. This introductory course will give an overview of the main concepts, techniques and algorithms that are relevant for the theory and practice of machine learning. The course will cover the fundamental topics of classification, regression and clustering, starting with simple learning models such as perceptrons, decision trees and logistic regression, and ending with more advanced models including Support Vector Machines, Conditional Random Fields and Bayesian networks. The description of the formal properties of the algorithms will be supplemented with motivating applications in a wide range of areas including natural language processing, computer vision, bioinformatics and music analysis. Requisites: Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Given a machine learning problem, students will be able to determine which of the studied algorithms is most appropriate. Students will be able to create new kernel functions and prove that particular functions satisfy kernel properties. Students will be able to implement simple learning algorithms such as kernel perceptrons and nearest neighbors. Students will be able to implement wrapper and filter methods for feature selection. Students will gain a basic understanding of sequential and statistical relational learning. Students will gain an understanding of classification with discriminative functions, probabilistic generative models and probabilistic discriminative models. Students will gain an understanding of major types of supervised learning, including regression and classification. Students will gain an understanding of supervised, unsupervised, and semi-supervised learning. Students will gain an understanding of the basic properties of Bayesian Networks. Students will gain an understanding of the kernel trick. Students will gain an understanding of the major principles of minimum squared error, maximum likelihood, maximum margin, and maximum entropy. Students will understand how to represent instances in machine learning as vectors of categorical or real-valued features. Students will understand major machine learning evaluation settings, including k-fold cross-validation. Students will understand the concept of overfitting and methods for reducing overfitting, such as quadratic regularization. Students will understand the importance of inductive bias in machine learning.
	CS 6840 - Natural Language Processing Natural Language Processing (NLP) is a branch of Artificial Intelligence that focuses on the design of computer systems for processing, understanding, or communicating in natural language. This graduate level course covers statistical and machine learning approaches for solving fundamental tasks in NLP, such as language modeling, part of speech tagging, syntactic parsing, word sense disambiguation, semantic role labeling, coreference resolution, and semantic parsing. Students will also learn about major applications of NLP, including information retrieval and web search, information extraction, question answering, machine translation, sentiment analysis, text mining, and speech recognition. Requisites: Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will be able to build language models for authorship attribution and language detection. Students will be able to implement the probabilistic CKY algorithm for unlexicalized syntactic parsing. Students will be able to use existing NLP packages to train and evaluate HMMs and CRFs for sequence tagging. Students will be able to use machine learning algorithms for word sense disambiguation. Students will be able to use statistical and neural techniques for developing language models. Students will be able to use Phrase Structure Grammars, Dependency Grammars, and Combinatory Categorial Grammars for syntactic parsing of text. Students will be able to apply basic text processing steps such as sentence segmentation, tokenization, and stemming. Students will be able to evaluate deterministic and learning-based algorithms for coreference resolution. Students will be able to use formal meaning representations based on lambda calculus and first order predicate logic. Students will be able to describe the significance of NLP in solving practical problems such as Information Retrieval, Information Extraction, and Question Answering. Students will be able to use third party packages to solve natural language processing problems.
	CS 6850 - Image Understanding Comprehensive study of image understanding and computer vision techniques. Topics include low-level image analysis methods, image formation, cameral calibration, edge detections, feature detection, region segmentation, color image segmentation, techniques for inferring three dimensional information from 2D images, and three dimensional object modeling and recognition. Requisites: Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will be able to apply image understanding techniques to specific 2D and 3D vision problems, including object recognition. Students will be able to compare and contrast low, mid, and high level computer vision algorithms. Students will be able to apply the mathematical foundations of geometric transformations and camera transformations. Students will be able to describe and design an advanced computer vision system.
	CS 6860 - Information Retrieval and Web Search This course covers the design, implementation, and evaluation of modern information retrieval (IR) systems, such as Web search engines. The course focuses on the underlying retrieval models, algorithms, and system implementations, such as vector-space and probabilistic retrieval models, as well as the PageRank algorithm used by Google. The course also covers more advanced topics in information retrieval, including document categorization and clustering, recommender systems, collaborative filtering, and personalized search. Requisites: Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will be able to build a basic Web search engine, starting from a Web crawler to a ranking model that integrates vector space measures with link analysis. Students will be able to build a basic Web interface for a Web search engine. Students will be able to evaluate the performance of IR systems. Students will be able to acquire knowledge of query expansion techniques and relevance feedback. Students will be able to use probabilistic IR models and language models for IR. Students will be able to use and compare analysis algorithms such as PageRank and Hubs and Authorities. Students will be able to implement text clustering and classification algorithms and explain their relevance for IR. Students will be able to implement major indexing techniques and evaluate their impact on query processing. Students will be able to summarize approaches for recommender systems and collaborative filtering. Students will be able to explain basic statistical properties of large text collections and evaluate their impact on the design of effective IR engines. Students will be able to explain Boolean retrieval models and their two major extensions: phrase search and proximity search. Students will be able to explain major techniques for personalized IR. Students will be able to use the vector space model approach for ranked information retrieval. Students will be able to explain the importance of natural language processing tools for IR, especially for language identification, tokenization, and word sense disambiguation. Students will be able to use third party packages for the implementation of indexing and search engines.
	CS 6890 - Deep Learning This course will introduce the multi-layer perceptron, a common deep learning architecture, and its gradient-based training through the backpropagation algorithm. Fully connected neural networks will be followed by more specialized neural network architectures such as convolutional neural networks (for images), recurrent neural networks (for sequences), and memory-augmented neural networks. The later part of the course will explore more advanced topics, such as generative adversarial networks and deep reinforcement learning. The lectures will cover theoretical aspects of deep learning models, whereas homework assignments will give students the opportunity to build and experiment with shallow and deep learning models, for which skeleton code will be provided. Requisites: CS 6830 or permission Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will be able to derive the gradients of a number of standard objective functions in machine learning, such as sum-of-square errors or cross-entropy. Students will be able to implement the backpropagation algorithm for feedforward neural networks. Students will be able to explain the advantages of deep learning architectures over shallow architectures. Students will be able to list the difficulties one may encounter when training deep architectures and outline solutions to alleviate them. Students will be able to use regularization techniques for deep architectures. Students will be able to summarize and evaluate recent state-of-the-art deep learning techniques. Students will be able to employ deep learning packages to complete a month-long machine learning project. Students will be able to design neural architectures appropriate for a given machine learning problem. Students will be able to evaluate the impact of hyper-parameters on the performance of neural models.
	CS 6900 - Special Topics in Computer Science Selected graduate level topics of current interest in computer science. Requisites: Credit Hours: 1 - 4 Repeat/Retake Information: May be repeated for a maximum of 12.0 hours. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will be able to meet the outcomes of the course as established by the instructor.
	CS 6910 - Graduate Internship in Computer Science Supervised work-related experience in government or industry Requisites: Permission required Credit Hours: 1 Repeat/Retake Information: May be repeated for a maximum of 2.0 hours. Lecture/Lab Hours: 2.0 field experience/internship Grades: Eligible Grades: F,CR,WP,WF,WN,FN,AU,I Learning Outcomes: Students will gain practical experience by participating in an external internship.
	CS 6930 - Independent Study Independent study in advanced topics of current interest in computer science. Requisites: Credit Hours: 1 - 4 Repeat/Retake Information: May be repeated for a maximum of 8.0 hours. Lecture/Lab Hours: 1.0 independent study Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will be able to meet the outcomes of the course as established by the student under the guidance of the instructor.
	CS 6940 - Research in Computer Science Research in computer science. Variable topics. Requisites: Credit Hours: 1 - 18 Repeat/Retake Information: May be repeated. Lecture/Lab Hours: 1.0 research Grades: Eligible Grades: F,CR,PR,WP,WF,WN,FN,AU,I Learning Outcomes: Students will be able to conduct independent research in computer science.
	CS 6950 - Thesis Thesis research and writing in computer science. Requisites: Credit Hours: 1 - 18 Repeat/Retake Information: May be repeated. Lecture/Lab Hours: 1.0 thesis/dissertation Grades: Eligible Grades: F,CR,PR,WP,WF,WN,FN,AU,I Learning Outcomes: Students will be able to write a computer science thesis.
	CS 6980 - Graduate Research Seminar Research seminar for graduate students in computer science. Requisites: Credit Hours: 1 Repeat/Retake Information: May be repeated for a maximum of 2.0 hours. Lecture/Lab Hours: 1.0 seminar Grades: Eligible Grades: F,CR,WP,WF,WN,FN,AU,I Learning Outcomes: Students will learn effective methods for giving research presentations. Students will learn research methods for advanced study in computer science.
	CSD 5000 - Aging and Disorders of Communication Natural patterns and disorders of communication in aging. Means of working with and advocating for elderly people with communication disabilities. Requisites: Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Delineate key areas of research pertaining to aid elderly people with communication disabilities. Demonstrate brain-behavior relationships in common disorders impacting adults. Describe normal and disordered communication in aging individuals. List means of advocacy for elderly people with communication disabilities.
	CSD 5110 - Elementary American Sign Language I This is the first in a sequence of six American Sign Language (ASL) courses. Course focuses on the foundational aspects of ASL such as the manual alphabet, various number systems, basic grammatical structure, non-manual grammatical markers, listing, ranking, contrastive structure, and the use of space. The course applies a conversational, deaf studies approach. The history and culture of the deaf community in the United States is introduced. Requisites: WARNING: No credit for this course if taken after CSD 5850 Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will be able to apply current research on deaf studies/American Sign Language (ASL) to individual areas of course study. Students will be able to comprehend and produce basic conversational norms such as introductions, describing relationships, self-disclosure, living situations, directions, daily routines using culturally appropriate social behaviors. Students will be able to demonstrate non-manual markers associated with yes/no questions, “wh” questions, negations, assertions, affect, topic- comment, rhetorical questions, and conditional sentences. Students will be able to identify the main idea or concept in basic conversations and narratives and themes central to deaf culture. Students will be able to express cardinal numbers 1-100, age numbers, ordinal numbers, time and ranking in ASL. Students will be able to comprehend and produce basic grammatical rules associated with ASL, for example, parameters, listing, contrastive structure, sign space, spatial referencing, and agreement verbs.
	CSD 5120 - Elementary American Sign Language II This is the second in a sequence of six American Sign Language (ASL) courses. Course continues to develop grammatical competency in regard to sentence structures in ASL. Course expands on concepts previously introduced and introduces classifiers and ASL literature. The course applies a conversational, deaf studies approach. Registered students attend a section of the corresponding undergraduate course. Requisites: CSD 5110 Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will be able to identify and produce verbs using appropriate spatial agreement. Students will be able to identify and produce grammatically appropriate statements, topic-comment, yes/no-questions, wh-questions, conditional, commands, negations, assertions and rhetorical sentence structures. Students will be able to effectively retell stories using one-person and two-person role-shifts, basic classifiers and will identify key characteristics of ASL Literature. Students will be able to comprehend and produce information regarding neighborhoods including giving and receiving directions. Students will be able to comprehend and produce requests, complaints and suggestions. Students will expand on ASL number systems and be able to comprehend and produce information regarding the year, time of day and money. Students will be able to apply current research on deaf studies/American Sign Language (ASL) to individual areas of course study.
	CSD 5210 - Intermediate American Sign Language I This is the third in a sequence of six American Sign Language (ASL) courses. Intermediate level ASL classes provide students opportunity to develop more complex expressive and receptive conversational skills. Emphasis is placed on expressive ASL using classifiers in ASL storytelling. Topics revolve around sharing information about the environment and everyday communication. Grammar is targeted in context with an emphasis on further development of discourse skills. Students learn conversational strategies to maintain more complex ASL conversations. This is a continued study of Deaf community and more complex ASL literature. Registered students attend a section of the second-year undergraduate course. Requisites: CSD 5120 or 5860 Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will be able to apply current research on deaf studies/American Sign Language (ASL) to individual areas of course study. Students will be able to demonstrate correct use of ASL classifiers at the intermediate level. Students will be able to correctly identify non-manual markers (facial expressions) for grammatical usage and spatial referencing. Students will be able to comprehend and produce finger spelled words and phrases of varied lengths at a fast speed. Students will be able to correctly use and comprehend numbers up to thousands in relation to money and numbers used with complex time (calendar) concepts. Students will be able to demonstrate advanced use of ASL directional verbs using temporal and distributional aspects of ASL in conversation. Students will be able to discuss information about Deaf Culture around the world. Students will be able to demonstrate how to apply different types of role shifting in an ASL discourse. Students will be able to demonstrate comprehension of information that is presented using complex grammatical features and higher-level vocabulary.
	CSD 5220 - Intermediate American Sign Language II The fourth in a sequence of six American Sign Language (ASL) courses. Focus is placed on the expressive use of ASL through storytelling. Expressive use of ASL grammar is expanded with an emphasis on developing questioning and answering skills. Conversational strategies are learned to help students maintain an ASL conversation appropriately. Includes English/ASL translation of concepts and stories. Requisites: CSD5210 Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will be able to apply current research on deaf studies/American Sign Language (ASL) to individual areas of course study. Students will be able to demonstrate the use of vocabulary necessary to talk about advanced topics using ASL. Students will be able to demonstrate the translation of concepts between English and ASL. Students will be able to identify and use multiple types of ASL classifiers and temporal/distributional features. Students will be able to use and comprehend numbers up to millions in relation to money and demonstrate use of various number systems in ASL discourse. Students will be able to incorporate different types of role shifting in telling narratives. Students will be able to maintain a conversation about life events in ASL. Students will be able to demonstrate their ability to translate written English into ASL and ASL into written English.
	CSD 5310 - Advanced American Sign Language I The fifth in the sequence of six American Sign Language (ASL) courses. The advanced level ASL classes provide students the opportunity to further develop more complex comprehension and production skills. This course is designed for students to develop greater knowledge and proficiency of American Sign Language and its subcomponents (e.g., vocabulary, morphology, grammar) and greater American Sign Language conversational proficiency. Emphasis is on ASL expression through language immersion within a controlled classroom of all signers. Requisites: CSD 5220 Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will be able to apply current research on deaf studies/American Sign Language (ASL) to individual areas of course study. Students will be able to demonstrate conversational fluency by discussing personal life experiences. Students will be able to discuss money with a focus on banking and financing. Students will be able to describe making major life decisions involving housing, vehicles, careers, etc. Students will be able to discuss making decisions regarding health conditions. Students will be able to demonstrate English to ASL signing skill of using visual-gestural depiction of selected vocabulary and grammar features of manual markers, role shifting, locatives, distributional, personification and temporal aspects of ASL.
	CSD 5320 - Advanced American Sign Language II The final class in the sequence of six American Sign Language (ASL) courses. The advanced level classes provide students the opportunity to further develop more complex comprehension and production skills in ASL. This course is designed for students to develop mastery knowledge and proficiency of ASL and its subcomponents (e.g., vocabulary, morphology, grammar) and conversational proficiency with deaf signers within the context of the deaf culture. Course represents the capstone of the ASL course sequence and thus requires students to demonstrate ASL proficiency in real life situations. Requisites: CSD 5310 Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will be able to apply current research on deaf studies/American Sign Language (ASL) to individual areas of course study. Students will be able to describe the value of ASL literature to the deaf community. Students will be able to incorporate the use of classifiers, role-shifting and non-manual markers in ASL storytelling. Students will be able to illustrate how to adapt written literature of fairytales and folktales to ASL version. Students will be able to demonstrate high level of production skills using correct grammatical structure through presentations and in a variety of discourse levels including real world applications. Students will be able to analyze, translate and produce conceptually accurate English idioms into ASL.
	CSD 5710 - Aural Rehabilitation Provides students with a basic understanding of rehabilitation principles and techniques used with children and adults with hearing impairments. Emphasis will be placed upon application of concepts to real life problems encountered with these populations. Requisites: Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Demonstrate knowledge of how hearing aids and other assistive listening technology can assist individuals with hearing loss. Demonstrate knowledge of the different communication options available for both adults and children who have hearing loss. Demonstrate knowledge of the different techniques used to develop auditory, speechreading and lipreading skills in individuals with hearing loss. Demonstrate knowledge of various communication disorders related to hearing.
	CSD 5860 - Sign Language II A continuation into the world of deafness and American Sign Language (ASL). We will expand on the learning of American Sign Language (ASL) vocabulary, continue the investigation of deaf culture and advance the analysis of language concepts learned in Sign Language 1. Use of classifiers and ASL idiomatic expressions are also discussed. Requisites: CSD 5850 Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Demonstrate a working knowledge and awareness of Deaf history, culture and the range of communications systems used by the American Deaf population. The student will correctly express information in ASL, based on vocabulary presented in the course text, chapters 7-12. The student will receptively comprehend information presented in ASL, as well as culture/language/history topics presented in class.
	CSD 5870 - Sign Language III A continuation into the world of deafness and American Sign Language (ASL). Students will continue the study of the cultural and language concepts learned in Sign Language 2. Emphasis is placed on expressive ASL through the use of classifiers and ASL idioms in ASL storytelling. Requisites: CSD 5860 Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: The student will demonstrate the ability to comprehend information presented in ASL and culture/language/history topics in print. The student will demonstrate the ability to express information presented in ASL.
	CSD 5900 - Special Topics in Communication Sciences and Disorders Specific course content will vary with offering. Requisites: Credit Hours: 1 - 15 Repeat/Retake Information: May be repeated. Lecture/Lab Hours: 1.0 lecture Grades: Eligible Grades: A-F,CR,PR,WP,WF,WN,FN,AU,I Learning Outcomes: Students will be able to evaluate how knowledge acquired in this course will be applicable to their work in the field of Communication Sciences and Disorders.
	CSD 6010 - Research Methods in Hearing, Speech and Language Sciences Designed to teach students to be critical consumers of published group and single subject design research in speech-language pathology and audiology. Topics include the scientific method, generating relevant research questions, various study designs, different data types, data analysis, and data interpretation. Requisites: Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Demonstrate knowledge of group design research via thru exam performance and submission of written critiques of published papers. Demonstrate knowledge of single subject design research by presenting power point presentations on selected topics and presenting a power point presentation of a single subject design study to answer a clinical case.
	CSD 6020 - Child Language Disorders I: Birth to Five First course in child language disorders sequence. In-depth study of language assessment and intervention strategies for young children with language delays and disorders. Therapy areas include prelinguistic communication skills, pragmatic skills, as well as semantic and grammatical aspects of comprehension and production. Early child cognition and emergent literacy will also be addressed. Requisites: Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: For a child at any age in the birth-to-five age range, students will explain that child’s typical linguistic attainments in semantics, pragmatics, morphology, syntax, and phonology. Students will integrate learned information to plan an appropriate diagnostic assessment for a communication-delayed infant, toddler, or preschooler and his/her family. Students will integrate learned information to plan an appropriate intervention program for a communication-delayed infant, toddler, or preschooler and his/her family.
	CSD 6030 - Neuroscience of Communication Provides complete study of neuroanatomy of the central nervous system and detailed instruction in anatomical structures and pathways of the central somatosensory, motor, auditory, vestibular, and visual systems. Hands-on experience in a neuroanatomy laboratory is emphasized. Functional aspects at the systems level are included and consequences of pathological lesions are discussed in forms of case studies. Requisites: Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will demonstrate knowledge of neurological bases of basic human communication processes as well as anatomy and physiology of the auditory and vestibular systems. Students will explain the structure and functions of the central nervous system to facilitate their future study of neurogenic communication disorders.
	CSD 6120 - Child Language Disorders II: School-age Language and Literacy Second course in child language disorders sequence. This course covers assessment and intervention theory and practice in the language domains for school-age children with language disorders. Emphasis is on language-literacy connections and language underpinnings in relation to academic content standards. Requisites: WARNING: No credit for both this course and the following (always deduct credit for first course taken): CSD 6190 Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will accurately identify syntactic and morphological patterns in school-age academic materials. Students will analyze a school-age textbook reading in assessment planning. Students will analyze a school-age textbook reading in intervention planning. Students will analyze a written language sample from a school-age child with language disorder. Students will evaluate common assumptions in the assessment and therapeutic practices for school-age children with language disorders. Students will explain the linguistic, metalinguistic, and metacognitive demands in a variety of academic content standards. Students will explain the speech-language pathologist’s role in reading development and comprehension. Students will identify appropriate service delivery models in case studies of children with language disorders. Students will summarize vocabulary teaching practices for school-age children with language disorders.
	CSD 6130 - Speech Sound Development and Disorders This course covers speech sound difficulties associated with overall language disorders. There is an emphasis on theories of speech sound acquisition, stages of development, description of deviant systems, methods of data collection and analysis, and treatment approaches. Requisites: Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will be able to apply key concepts of phonology and phonetics to individuals with speech/sound disorders. Students will be able to conduct an evaluation of a child with a speech sound disorder. Students will be able to describe the etiological factors and conditions related to typical and disordered phonology and speech sound production. Students will be able to identify and describe typical and atypical speech/sound development/ diagnose speech sound disorders. Students will be able to make appropriate therapy decisions including the identification and justification of the appropriate goals,target selection, and therapy techniques. Students will be able to transcribe and analyze typical and disordered speech patterns.
	CSD 6170 - Disorders of Fluency Focus is on the speech disorder of stuttering as related to theory, research, assessment, and remediation. Requisites: Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will demonstrate detailed knowledge about intevention for fluency disorders. Students will demonstrate detailed knowledge about the assessment of fluency disorders. Students will demonstrate fundamental knowledge about the nature of fluency disorders.
	CSD 6190 - Speech Language Pathology in Public Schools Assessment, intervention, and administrative issues for speech-language pathologists working with children in the public schools. Requisites: WARNING: No credit for both this course and the following (always deduct credit for first course taken): CSD 6120 Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will demonstrate knowledge of administrative issues related to working as a speech-language pathologist in a public school. Students will demonstrate knowledge of assessment strategies for school-age children. Students will demonstrate knowledge of intervention strategies for school-age children. Students will demonstrate knowledge of typical school-age development in language and literacy. Students will explain the the relationship and influences of a language disorder on literacy.
	CSD 6210 - Disorders of Phonation Review of anatomy and normal physiology of vocal mechanism. Organic and functional voice problems and related therapy. Research problems in diagnosis and therapy. Requisites: Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: To demonstrate knowledge in the identification and assessment of the different types of voice disorders. To demonstrate knowledge of the implementation of management programs for the patients with voice disorders. To explain the anatomy and physiology of the vocal mechanism.
	CSD 6220 - Child Language Disorders III: School-age Psycholinguistic Perspectives Third course in child language disorders sequence. This course explores the psycholinguistic underpinnings of language impairment in school age children. Requisites: Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will demonstrate knowledge about the primary cognitive-linguistic deficits in school age children via a) exam performance and b) presentation of a clinical case study. Students will demonstrate knowledge of the best practices in the assessment, diagnosis and treatment of the cognitive-linguistic impairments in school age children via a) exam performance and b) presentation of a clinical case study.
	CSD 6230 - Diagnostic Procedures in Speech-Language Pathology Study of theory and practice pertaining to the diagnostic process, including topics on models of diagnosis, family-centered assessment, multicultural issues, tools and methods, as well as assessment in selected areas of disorders. Requisites: Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will engage in interviewing, observing, and testing and to integrate obtained data. Students will describe the construction, use and value of psychometric tests. Students will explain the basic components of the diagnostic process and models of diagnosis. Students will present diagnostic information and results in a clear and appropriate written format.
	CSD 6240 - Neuromotor Disorders of Speech In-depth study of nature and habilitation of speech disorders of organic etiology. Primary focus on articulation disorders resulting from structural lesions, muscle incoordination, and weakness. Requisites: Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will demonstrate knowledge and skills pertaining to neurological bases of motor speech disorders. Students will demonstrate knowledge of the implementation of management programs for patients with motor speech disorders. Students will demonstrate knowledge of differential diagnosis of motor speech disorders.
	CSD 6250 - Pediatric Feeding: Assessment and Intervention This course addresses the theoretical, clinical and multicultural aspects of the role of the speech-language pathologist with children with feeding and/or swallowing disorders. Requisites: CSD 6020 Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will be able to identify the ethical and efficacy issues involved with feeding and swallowing disorders in the pediatric population. Students will be able to investigate adequate and developmentally appropriate nutrition for the pediatric population. Students will be able to discuss aspects of cultural diversity as it relates to dysphagia assessment, treatment and counseling for children with pediatric feeding disorders and their families. Students will be able to apply knowledge and skills in the assessment and treatment and management of feeding and swallowing disorders in the pediatric population.
	CSD 6260 - Counseling and Interviewing in Communication Sciences and Disorders Study of counseling and interviewing in audiology and speech-language pathology. Practice of interviewing and counseling techniques used during the assessment and treatment of hearing, speech and language disorders. Requisites: Credit Hours: 2 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 2.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will be able to apply key concepts of counseling and interviewing to clients/patients with hearing, speech and language impairments. Students will be able to conduct an interview with individuals with hearing, speech or language impairments and their family members. Students will be able to conduct a counseling session with individuals with hearing, speech or language impairments and their family members. Students will be able to summarize their own philosophy of counseling and interviewing.
	CSD 6270 - Medical Aspects of Auditory Disorders Provides discussion of etiology, pathophysiology, diagnosis, and medical and surgical treatments for the various external, middle, inner ear, and central nervous system diseases that result in a variety of auditory disorders. Overview of recent advances in molecular biology and genetics of hearing loss. Readings in medical literature and familiarization with medical terminology and philosophy of intervention. Requisites: CSD 6730 and 6731 and 6750 and 6770 Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will be able to demonstrate comprehension of otological and audiological diagnosis and management of hearing disorders. Students will be able to demonstrate knowledge of embryologic development and malformation related to the auditory system. Student will be able to demonstrate knowledge of genetics and molecular biology of hearing loss.
	CSD 6290 - Adult Language Disorders Theory, etiology, diagnostics, treatment methods, and service delivery issues related to adult neurogenic language disorders. Includes study of aphasia, dyslexia, dysgraphia, right hemisphere deficits, frontal lobe syndromes, traumatic brain injury, and dementia. Requisites: CSD 6030 Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Demonstrate awareness of the ways in which neurogenic communication disorders may affect the lives of patients and their friends and families. Demonstrate knowledge of pertinent professional practice issues that affect the delivery of clinical services to persons with neurogenic communication disorders. Demonstrate knowledge of treatment issues and methods for application in clinical work with patients who have neurogenic language disorders. Describe appropriate diagnostic processes and prognostic considerations for application in clinical work with patients who have neurogenic language disorders. Describe the etiology and symptomatology associated with a wide variety of neurogenic language disorders.
	CSD 6340 - Clinical Methods in Speech-Language Pathology Addresses the specific clinical skills and abilities for clinical practice in communication disorders, including technical writing, cultural competency, interview skills, treatment efficacy, diagnostic skills, self-analysis/self-evaluation, steps in licensure/certification, professional development, ethical practice, and specific therapy strategies for several communication disorders. Requisites: Credit Hours: 2 Repeat/Retake Information: May be repeated for a maximum of 8.0 hours. Lecture/Lab Hours: 2.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: To demonstrate competencies in evidence based decision making in clinical practice. To demonstrate knowledge and skills in self-analysis and self-evaluation of clinical skills. To demonstrate knowledge of professionalism and abilities needed for exemplary clinical practice. To develop and practice appropriate technical writing skills for clinical practice. To develop and practice culturally competent skills for appropriate clinical practice. To discuss the steps needed to become a licensed/certified professional.
	CSD 6351 - Professional Education in Audiology I Designed to bridge didactic coursework and clinical experience for first year Au.D. students. Lecture, practice, experimentation,and student presentations. Topics coincide with courses and level of the students. Requisites: Credit Hours: 2 Repeat/Retake Information: May be repeated for a maximum of 6.0 hours. Lecture/Lab Hours: 2.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Demonstrate knowledge of ethical issues within the field of audiology. Demonstrate knowledge of current topics and issues within the field of audiology. Demonstrate knowledge of various clinical procedures within the field of audiology through discussion, demonstration, presentation, labs, mock patients and case studies.
	CSD 6400 - Augmentative Communication Study of augmentative communication and assistive listening systems. Development of skills in the application of augmentative communication to communication disorders in adults and children. Experience with microprocessor-based technology. Requisites: Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Critically evaluate strengths and weaknesses of different AAC systems, devices, vocabulary and models of service delivery for individuals with complex communication needs. Describe and summarize characteristics of individuals who may benefit from AAC. Design setting-appropriate intervention plans with measurable and achievable goals that meet individual client needs. Develop case history/interview questions for clients and communication partners. Identify, describe, and critically evaluate skills (including linguistic, operational, social, and strategic skills as well as mediating factors) required to build communicative competence and use of (un)aided AAC systems Interpret, integrate, and synthesize information to make appropriate recommendations for intervention. Justify appropriate AAC systems, devices, vocabulary, and models of service delivery to meet the needs of individuals with complex communication needs. Modify evaluation procedures to meet individual client needs. Select appropriate evaluation procedures (e.g., behavioral observations, non-standardized and standardized tests, and instrumental procedures). Select or develop appropriate materials for intervention. Summarize appropriate and consumer-responsive AAC assessment goals, procedures, and tools to identify communication needs of individuals who require AAC, to assess their skills ( consideration of physical, cognitive, linguistic, social factors) Summarize appropriate and consumer-responsive vocabulary selection processes for individuals who use alternative communication modalities (including consideration of the physical, cognitive, linguistic, social, and cultural correlates)
	CSD 6410 - Dysphagia Basic knowledge of normal and deviant swallowing disorders due to neurological and structural impairments. Major topics include assessment and management of the wide range of swallowing disorders managed by speech-language pathologists. Requisites: Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will demonstrate knowledge and skills related to normal swallowing physiology in children and adults and the effects of aging. Students will describe compensation and rehabilitation strategies for dysphagic individuals with a variety of etiologies.. Students will explain evaluation methods for individuals of different ages utilizing current, clinically-applicable methods..
	CSD 6520 - Experimental Phonetics Speech communication involves the generation of sounds by a speaker from some internal linguistic representations and the interpretation of sounds by a listener. Explores how linguistic representations are implemented by the speaker to generate sounds and how the acoustic signal is perceived by the listener to uncover linguistic representations. Requisites: Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Demonstrate knowledge of normal processes of speech and language production and perception. Demonstrate knowledge of the acoustic and linguistic bases of basic human communication processes. Demonstrate knowledge of the principles, methods, and applications of psychoacoustics.
	CSD 6730 - Diagnostic Audiology Presents fundamental and advanced audiological procedures for the diagnosis of conductive, cochlear, and eight nerve disorders of the auditory systems. Lab experiences will provide hands-on experience with current test protocols and equipment. Requisites: Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Demonstrate knowledge of effective documentation as well as verbal and written communication of procedures, results, recommendations, referrals, and progress (if applicable) to patients, families, and other appropriate individuals. Demonstrate knowledge of the proper selection, administration, and interpretation of audiologic assessments based on knowledge of auditory anatomy and physiology, pathophysioogy of common auditory disorders, and patient characteristics/case history. Demonstrate understanding of the proper use and calibration of equipment consistent with manufacturer’s recommendations and specifications as well as safety factors. Demonstrate understanding of the laws, regulations, policies, and management practices relevant to the profession of audiology.
	CSD 6731 - Advanced Diagnostic Audiology Presents advanced audiological procedures for the differential diagnosis of auditory disorders including those of the central auditory system and facial nerve as well as procedures for constructing and evaluating assessment protocols. Lab provides hands-on experience with current test protocols and equipment. Requisites: CSD 6730 Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will be able to recognize non-organic hearing loss and ways to approach hearing assessment in persons exhibiting such responses. Students will be able to describe research in the field through in class presentations of journal articles as well as a group protocol development presentation in a selected area of audiology. Students will be able to demonstrate an understanding of the conceptual formation as well as the execution of behavioral tests for central auditory diagnostic assessment. Students will be able to demonstrate knowledge of the theory behind and procedures for test protocol development, implementation, and revision. Students will be able to interpret test findings to arrive at a probable diagnosis of auditory pathology for common or frequently discussed disorders of the peripheral and central auditory system as well as the facial nerve.
	CSD 6740 - Hearing Aids Fundamental aspects of hearing aid form, function, fit, and verification are introduced. Topics germane to hearing aid dispensing such as counseling, prescriptive gain, fitting strategies, programming, and trouble shooting are discussed and practiced. Requisites: CSD 6730 and 6770 Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Demonstrate knowledge of earmold acoustics and modification techniques. Demonstrate knowledge of hearing aid counseling, fitting, prescription, and trouble shooting. Demonstrate knowledge of the components of a modern hearing aid and its role in sound processing. Demonstrate knowledge of the features and uses of linear and non-linear hearing aids. Demonstrate knowledge on how to measure and interpret the electroacoustic parameters of a hearing aid. Demonstrate knowledge on the use of expansion in hearing aids. Recognize the difference between analog and digital signal processing (DSP).
	CSD 6749 - Electrophysiologic Assessment Electrophysiologic measurements applied to human auditory system function focused on the use of auditory evoked potentials. Requisites: CSD 6730 Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will be able to demonstrate knowledge of the calibration and set up of auditory evoked potential equipment. Students will be able to demonstrate functional knowledge of auditory brainstem response assessment and interpretation. Students will be able to demonstrate fundamental knowledge regarding electrocochleography and middle and late evoked responses. Students will be able to demonstrate knowledge of advances in brainstem evoked potential assessments.
	CSD 6750 - Electrophysiologic Assessment Electrophysiologic measurements applied to human auditory system function focused on the use of auditory evoked potentials. Requisites: CSD 6730 Credit Hours: 4 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 4.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will be able to demonstrate knowledge in calibration, setup, measurement, and interpretation of advanced audiotory electrophysiologic tests. Students will be able to demonstrate knowledge of how results on advanced electrophysiologic tests are affected by various pathologies.
	CSD 6751 - Advanced Electrophysiologic Assessment Advanced topics in auditory electrophysiologic assessment including topics such as frequency following response, P300, mismatch negativity as well as other early-, mid-, and late-evoked potentials. Requisites: CSD 6750 Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Demonstrate knowledge in calibration, setup, measurement, and interpretation of advanced audiotory electrophysiologic tests. Demonstrate knowledge of how results on advanced electrophysiologic tests are affected by various pathologies.
	CSD 6770 - Advanced Hearing Science Overview of classical and contemporary psychophysical methods, physics of sound, anatomy and physiology of the auditory system, excitation of cochlea and auditory nerve, frequency analysis, pitch perception, nonlinear distortion, loudness, frequency, and intensity discrimination. Requisites: Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Demonstrate knowledge of auditory anatomy and physiology and pathophysiology. Demonstrate knowledge of the psychoacoutic principles and procedures.
	CSD 6900 - Special Topics in Speech-Language Pathology Varied topics relating to special clinical, professional, and theoretical topics in speech-language pathology. Requisites: Credit Hours: 1 - 3 Repeat/Retake Information: May be repeated for a maximum of 15.0 hours. Lecture/Lab Hours: 3.0 seminar Grades: Eligible Grades: A-F,CR,PR,WP,WF,WN,FN,AU,I Learning Outcomes: Students will be able to describe theoretical viewpoints in communication development and disorders. Students will demonstrate detailed knowledge of professional issues in speech-language pathology. Students will demonstrate knowledge of asessment and intervention methods, as appropriate per topic. Students will demonstrate knowledge of procedures and methods, as appropriate per clinical topic. Students will describe, in detail, clinical populations as related to each clinical topic.
	CSD 6901 - Special Topics in Speech-Language pathology Varied topics relating to clinical, professional and theoretical topics in speech-language pathology. Requisites: Credit Hours: 1 - 3 Repeat/Retake Information: May be repeated for a maximum of 15.0 hours. Lecture/Lab Hours: 3.0 seminar Grades: Eligible Grades: A-F,CR,PR,WP,WF,WN,FN,AU,I Learning Outcomes: Students will be able to describe theoretical viewpoints in communication development and disorders. Students will demonstrate knowledge of assessment and intervention methods, as appropriate per topic. Students will demonstrate knowledge of procedures and methods, as appropriate per topic. Students will demonstrate knowledge of professional issues and topics in speech-language pathology. Students will describe, in detail, clinical populations as related to each clinical topic.
	CSD 6902 - Special Topics in Speech-Language Pathology Varied topics relating to clinical, professional, and theoretical topics in speech-language pathology. Requisites: Credit Hours: 1 - 3 Repeat/Retake Information: May be repeated for a maximum of 15.0 hours. Lecture/Lab Hours: 3.0 seminar Grades: Eligible Grades: A-F,CR,PR,WP,WF,WN,FN,AU,I Learning Outcomes: Students will be able to describe theoretical viewpoints in communication development and disorders. Students will demonstrate knowledge of assessment and intervention methods, as appropriate per topic. Students will demonstrate knowledge of procedures and methods, as appropriate per topic. Students will demonstrate knowledge of professional issues and topics in speech-language pathology. Students will describe, in detail, clinical populations as related to each clinical topic.
	CSD 6910 - Clinical Externship Full-time placement at an off-campus site (clinic, hospital or other medical facility, private practice, or in a school setting) involving all aspects of the clinical process in speech-language pathology. Requisites: (CSD 6080 or 6220) and 6130 and 6170 and 6210 and 6230 and 6290 and (Knowledge and Skill Assessment score in consistent range 5.0-6.9) Credit Hours: 2 - 15 Repeat/Retake Information: May be repeated for a maximum of 45.0 hours. Lecture/Lab Hours: 40.0 field experience/internship Grades: Eligible Grades: A-F,CR,PR,WP,WF,WN,FN,AU,I Learning Outcomes: Students will be able to demonstrate specific diagnostic skills and abilities for clinical practice in speech-language pathology. Students will be able to apply knowledge of specific intervention skills and abilities for clinical practice in speech-language pathology.
	CSD 6920 - Practicum in Diagnosis and Therapy Supervised clinical experience includes practice in diagnosis, planning of therapy, and remediation. Requisites: Credit Hours: 1 Repeat/Retake Information: May be repeated for a maximum of 6.0 hours. Lecture/Lab Hours: 10.0 practicum Grades: Eligible Grades: A-F,CR,PR,WP,WF,WN,FN,AU,I Learning Outcomes: Students will demonstrate skill in specific diagnostic practices needed to become a speech-language pathologist. Students will demonstrate skill in specific intervention practices needed to become a speech-language pathologist.
	CSD 6921 - Audiology Practicum I Experience in audiology diagnosis and aural rehabilitation in on-campus clinical and off-campus settings for first year Au.D. students. Requisites: Credit Hours: 1 - 2 Repeat/Retake Information: May be repeated for a maximum of 9.0 hours. Lecture/Lab Hours: 8.0 practicum Grades: Eligible Grades: A-F,CR,PR,WP,WF,WN,FN,AU,I Learning Outcomes: Students will demonstrate knowledge and proficiency in clinical audiology consistent with their current academic level as determined by the knowledge and skills aquisition guidelines established by the certification body and audiology faculty.
	CSD 6935 - Aging and Communication in the Developing World Exploration of aging and communication in the context of development. Includes global perspectives on health and health care access as they impact elderly adults in regions undergoing development. Requisites: Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 seminar Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Demonstrate understanding of the impact of health care access to older adults with and without disabilities. Describe needs for further research and advocacy to support underserved elderly individuals with communication challenges. Identify challenges to aging adults in at least three different regional development contexts. List means of advocating for elderly adults with communication disabilities in underserved regions.
	CSD 6950 - Thesis Thesis in communication disorders. Requisites: Permission required and successful defense of research proposal Credit Hours: 1 - 3 Repeat/Retake Information: May be repeated for a maximum of 12.0 hours. Lecture/Lab Hours: 3.0 thesis/dissertation Grades: Eligible Grades: A-F,CR,PR,WP,WF,WN,FN,AU,I Learning Outcomes: Student will conduct analysis and interpretation of data/findings. Student will engage in critical analysis and interpretation of data/findings. Student will recruit participants for a research study.
	CSD 7250 - Administration of Public School Speech-Language Pathology Programs Designed to prepare students to work as speech-language pathologists (SLPs) in public schools, this course includes issues involving the administration and implementation of speech-language programs in the public school system. The course focuses on SLP roles and responsibilities in schools in relation to legislation, evaluation team reports, individualized education programs (IEPs), procedural safeguards, and workload/caseload. Course also addresses the role the SLP in the wider context of being a member in a school learning community. Requisites: CSD 6120 Credit Hours: 1 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 1.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will be able to demonstrate knowledge of ETR (Evaluation Team Report) and IEP (Individualized Education Program) development. Students will be able to explain how historical events and legislation have influenced the roles and responsibilities of speech-language pathologists in the public schools. Students will be able to identify relevant and applicable procedural safeguards given various case scenarios. Students will be able to evaluate a typical caseload utilizing concepts related to workload. Students will be able to describe best practices in communication with school personnel. Students will be able to explain how a speech-language pathologist is a critical team member of a school learning community.
	CSD 7351 - Professional Education in Audiology II Designed to bridge didactic coursework and clinical experience for second year Au.D. students. Lecture, practice, experimentation, and student presentations. Topics coincide with courses and level of the students. Requisites: Credit Hours: 2 Repeat/Retake Information: May be repeated for a maximum of 4.0 hours. Lecture/Lab Hours: 2.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Demonstrate knowledge of current topics and issues within the field of audiology. Demonstrate knowledge of ethical issues within the field of audiology. Demonstrate knowledge of various clinical procedures within the field of audiology through discussion, demonstration, presentation, mock patients and case studies.
	CSD 7352 - Professional Education in Audiology II Designed to bridge didactic coursework and clinical experience for second year Audiology students. Requisites: Warning: No CSD 7351 Credit Hours: 3 Repeat/Retake Information: May be repeated for a maximum of 6.0 hours. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will be able to demonstrate knowledge of current issues in the field of audiology Students will be able to demonstrate knowledge of ethical issues in the field of audiology Students will be able to demonstrate knowledge of clinical procedures in the field of audiology
	CSD 7620 - Rehabilitative Audiology Prepares audiologists to structure and execute programs of (re)habilitation for individuals with hearing loss in clinical, vocational and/or educational settings as well as understand the psychosocial aspects of hearing loss. Requisites: (CSD 6730 or 673A) and (6740 or 674A) and (7630 or 763) Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will be able to demonstrate knowledge of different techniques used to develop auditory, speechreading and lipreading skills in individuals with hearing loss. Students will be able to demonstrate knowledge of the different communication options available for both adults and children who have hearing loss. Students will be able to demonstrate knowledge of the educational and vocational options for individuals with hearing loss. Students will be able to demonstrate knowledge of the habilitation and rehabilitation options for children and adults with hearing loss. Students will be able to demonstrate knowledge of the psychological and social effects of acquired and longstanding hearing loss. Students will be able to demonstrate knowledge on how to develop an aural (re)habilitation plan for both children and adults. Students will be able to discuss the attitudes of society towards hearing loss and deafness. Students will be able to explain the effects of acquired hearing loss on couples and families.
	CSD 7630 - Pediatric/Educational Audiology Discussions will cover the embryologic development of the auditory system, audiometric evaluation of infants and children, counseling and educational issues of children identified with hearing loss, pathological conditions and syndromes affecting the pediatric population, and issues germane to pediatric hearing aid selection and verification. Requisites: Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,CR,PR,WP,WF,WN,FN,AU,I Learning Outcomes: Students will be able to describe typical auditory embryologic development and factors affecting communication and auditory development in the pediatric population. Students will be able to implement the universal newborn hearing protocol for assessment and rehabilitation. Students will be able to apply knowledge of family needs when counseling newly identified children with hearing loss. Students will be able to describe the federal and state school legislation for children with hearing loss. Students will be able to describe the roles and responsibilities of a school audiologist. Students will be able to implement hearing screening protocols in school settings. Students will be able to appraise the educational needs of children with hearing loss and related communication disorders. Students will be able to justify the selection of a hearing aid for a pediatric patient. Students will be able to interpret expected auditory behavioral and non-behavioral responses of the pediatric population.
	CSD 7680 - Noise Exposure and Hearing Conservation Information about the adverse effects of noise on hearing and vestibular anatomy, noise control and measurement in occupational and non-occupational settings, hearing protection devices, and hearing conservation in recreational and educational settings. Also includes Occupational Safety and Health Administration (OSHA) regulations on noise exposure, regulations on compensation for industrial workers with noise-induced hearing loss, and the implementation of hearing conservation programs as prescribed by the National Institute for Occupational Safety and Health (NIOSH). Requisites: CSD 6730 and 6740 and 6770 Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will be able to demonstrate a working knowledge of the effects of the auditory and non-auditory effects of sound exposure on humans. Students will be able to demonstrate knowledge of OSHA regulations and instrumentation for noise measurement. Students will be able to describe potential human performance and health hazards related to excessive noise exposure. Students will be able to describe the general evaluation and acoustic treatments and hearing protection devices available for various acoustic environments. Students will be able to demonstrate a working knowledge of the key components of an industrial hearing conservation program and their implementation. Students will be able to demonstrate a working knowledge of noise exposure levels in non-occupational settings. Students will be able to demonstrate working knowledge of the rules and regulations related to compensation for industrial workers with noise-induced hearing loss.
	CSD 7700 - Cochlear Implants Neurobiological basis for cochlear implants, speech processing techniques, candidacy for implants, post operative management, and outcomes assessment. Requisites: (CSD 6030 or 603) and (6750 or 675A) and (6770 or 677) Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will demonstrate knowledge of the neurobiologic basis for cochlear implants and speech processing strategies in current devices. Students will demonstrate proficiency in audiologic and medical assessment of candidacy for cochlear implants and use of cochlear implant hardware and software
	CSD 7750 - Advanced Hearing Aids Advanced topics in hearing aid technology including compression, noise reduction strategies, directional microphone, class amplification technology, understanding performance of the damaged auditory system, and how advanced signal processing strategies might be used to compensate for these deficits. Requisites: Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Demonstrate knowledge of advanced hearing aid technologies. Demonstrate knowledge of how advanced hearing aid technologies assist persons with hearing loss.
	CSD 7850 - Balance Function Assessment Assessment of balance function including anatomy and physiology, theory, disorders and test protocols. Requisites: CSD 6030 and 6750 Credit Hours: 3 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 3.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will be able to identify the anatomy of the normal and abnormal peripheral and central vestibular system. Students will be able to describe the anatomy and physiology of the normal and abnormal peripheral and central vestibular system. Students will be able to identify normal and abnormal balance characteristics. Students will be able to use vestibular case history and questionnaires to make clinical decisions on appropriate assessment, treatment, and referral. Students will be able to demonstrate knowledge of the selection and administration and interpretation of bedside vestibular screening measures. Students will be able to demonstrate knowledge of the selection, administration, and interpretation of bedside vestibular screening measures and vestibular assessments. Students will be able to demonstrate use of basic methods of equipment calibration and safety precautions that are consistent with manufacturer recommendation and specifications. Students will be able to discuss different disorders of the peripheral and central vestibular system. Students will be able to demonstrate knowledge of treatment options with a specific focus on treatment of the nine paroxysmal positional vertigo.
	CSD 7910 - Clinical Externship in Audiology Experience in hearing testing, fitting hearing aids, diagnostic procedures related to hearing and balance, writing clinical reports, maintaining clinical facilities, and interacting with other professionals usually in an external clinical setting. Requisites: Credit Hours: 4 - 15 Repeat/Retake Information: May be repeated for a maximum of 30.0 hours. Lecture/Lab Hours: 40.0 field experience/internship Grades: Eligible Grades: A-F,CR,PR,WP,WF,WN,FN,AU,I Learning Outcomes: Students will demonstrate knowledge and proficiency in aural rehabilitation consistent with their current level of training and coursework. Students will demonstrate knowledge and proficiency in clinical audiology consistent with their current level of training and coursework. Students will demonstrate knowledge and proficiency in hearing aid fitting and selection consistent with their current level of training and coursework.
	CSD 7921 - Audiology Practicum II Experience in audiological diagnosis through direct patient contact, hearing aids, and aural rehabilitation in on-campus and off-campus settings for second year Au.D. students. Requisites: 2nd year Au.D. student Credit Hours: 1 - 3 Repeat/Retake Information: May be repeated for a maximum of 9.0 hours. Lecture/Lab Hours: 12.0 practicum Grades: Eligible Grades: A-F,CR,PR,WP,WF,WN,FN,AU,I Learning Outcomes: Students will demonstrate knowledge and proficiency in aural rehabilitation consistent with their current level of training and coursework. Students will demonstrate knowledge and proficiency in diagnostic audiology consistent with their current level of training and coursework. Students will demonstrate knowledge and proficiency in hearing aid fitting and selection consistent with their current level of training and coursework.
	CSD 7930 - Directed Studies Directed studies on selected topics in audiology or speech-language pathology. Requisites: Permission required Credit Hours: 1 - 6 Repeat/Retake Information: May be repeated for a maximum of 18.0 hours. Lecture/Lab Hours: 6.0 independent study Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will be able to demonstrate advanced knowledge in an area germane to audiology or speech-language pathology.
	CSD 7931 - Directed Studies Directed studies on selected topics in audiology of speech-language pathology. Requisites: Permission required Credit Hours: 1 - 6 Repeat/Retake Information: May be repeated for a maximum of 18.0 hours. Lecture/Lab Hours: 6.0 independent study Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will be able to demonstrate advanced knowledge in an area germane to audiology or speech-language pathology.
	CSD 7932 - Directed Studies Directed studies on selected topics in audiology or speech-language pathology. Requisites: Permission required Credit Hours: 1 - 6 Repeat/Retake Information: May be repeated for a maximum of 18.0 hours. Lecture/Lab Hours: 6.0 independent study Grades: Eligible Grades: A-F,CR,PR,WP,WF,WN,FN,AU,I Learning Outcomes: Students will be able to demonstrate advanced knowledge in an area germane to audiology or speech-language pathology.
	CSD 7950 - Integrated Clinical Education Designed to bridge didactic coursework and clinical experience for advanced-level students in the Audiology program. Requisites: Credit Hours: 1 Repeat/Retake Information: May not be retaken. Lecture/Lab Hours: 1.0 seminar Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Students will be able to demonstrate knowledge of current topics and issues within the field of audiology. Students will be able to demonstrate knowledge of ethical issues within the field of audiology. Students will be able to demonstrate knowledge of various clinical procedures within the field of audiology.
	CSD 8351 - Professional Education in Audiology III Designed to provide third year Au.D. students a didatic forum facilitating intergration of theorectical and clinical apects of diagnostic and rehabilitative audiology via lectures, practice, experimentation,and student participation and presentations. Topics covered will coincide with current and previous coursework as well as the level of the students. Requisites: Credit Hours: 2 Repeat/Retake Information: May be repeated for a maximum of 4.0 hours. Lecture/Lab Hours: 2.0 lecture Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I Learning Outcomes: Demonstrate knowledge of current topics and issues within the field of audiology. Demonstrate knowledge of ethical issues within the field of audiology. Demonstrate knowledge of various clinical procedures within the field of audiology through discussion, demonstration, presentation, mock patients and case studies.
	CSD 8900 - Special Topics in Communication Sciences and Disorders Specific course content will vary with offering. Requisites: Credit Hours: 1 - 15 Repeat/Retake Information: May be repeated. Lecture/Lab Hours: 1.0 lecture Grades: Eligible Grades: A-F,CR,PR,WP,WF,WN,FN,AU,I Learning Outcomes: Students will demonstrate advanced knowledge in an area germane to audiology or speech-language pathology.
	CSD 8910 - Full-time Audiology Externship Full-time supervised externship for three semesters, located nationwide. Requisites: CSD 8921 and 8949 must be completed prior to commencing externship Credit Hours: 4 - 15 Repeat/Retake Information: May be repeated for a maximum of 45.0 hours. Lecture/Lab Hours: 40.0 field experience/internship Grades: Eligible Grades: A-F,CR,PR,WP,WF,WN,FN,AU,I Learning Outcomes: Students will demonstrate knowledge and proficiency in aural rehabilitation consistent with an entry level, practicing audiologist. Students will demonstrate knowledge and proficiency in diganostic audiology consistent with an entry level, practicing audiologist. Students will demonstrate knowledge and proficiency in hearing aid fitting and selection consistent with an entry level, practicing audiologist.
	CSD 8921 - Audiology Practicum III Experience in audiological diagnosis through direct patient contact, hearing aids, and aural rehabilitation in on-campus and off-campus settings for third year Au.D. students. Requisites: Credit Hours: 1 - 3 Repeat/Retake Information: May be repeated for a maximum of 9.0 hours. Lecture/Lab Hours: 12.0 practicum Grades: Eligible Grades: A-F,CR,PR,WP,WF,WN,FN,AU,I Learning Outcomes: Students will demonstrate knowledge and proficiency in aural rehabilitation consistent with their current level of training and coursework. Students will demonstrate knowledge and proficiency in diganostic audiology consistent with their current level of training and coursework. Students will demonstrate knowledge and proficiency in hearing aid fitting and selection consistent with their current level of training and coursework.

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Courses

CS 5440 - Data Communications

CS 5500 - Advanced Object Oriented Design and GUI Techniques

CS 5560 - Software Design and Development I

CS 5580 - Operating Systems II

CS 5610D - Data Structures

CS 5620 - Database Systems

CS 5750 - Internet Engineering

CS 5800 - Artificial Intelligence

CS 5830 - Machine Learning

CS 5900 - Special Topics in Computer Science

CS 6040 - Advanced Algorithms

CS 6050 - Parallel Computation Theory

CS 6060 - Computational Complexity

CS 6120 - Real Time Systems

CS 6150 - Computational Genomics

CS 6250 - Computer Graphics and Visualization

CS 6410 - Medical Image Analysis

CS 6420 - Artificial Intelligence in Medicine

CS 6440 - Advanced Topics in Computer Networking

CS 6571 - Software Specification

CS 6572 - Software Design

CS 6573 - Software Implementation

CS 6800 - Advanced Topics in Artificial Intelligence

CS 6820 - Artificial Intelligence: Case-Based Reasoning

CS 6830 - Machine Learning

CS 6840 - Natural Language Processing

CS 6850 - Image Understanding

CS 6860 - Information Retrieval and Web Search

CS 6890 - Deep Learning

CS 6900 - Special Topics in Computer Science

CS 6910 - Graduate Internship in Computer Science

CS 6930 - Independent Study

CS 6940 - Research in Computer Science

CS 6950 - Thesis

CS 6980 - Graduate Research Seminar

CSD 5000 - Aging and Disorders of Communication

CSD 5110 - Elementary American Sign Language I

CSD 5120 - Elementary American Sign Language II

CSD 5210 - Intermediate American Sign Language I

CSD 5220 - Intermediate American Sign Language II

CSD 5310 - Advanced American Sign Language I

CSD 5320 - Advanced American Sign Language II

CSD 5710 - Aural Rehabilitation

CSD 5860 - Sign Language II

CSD 5870 - Sign Language III

CSD 5900 - Special Topics in Communication Sciences and Disorders

CSD 6010 - Research Methods in Hearing, Speech and Language Sciences

CSD 6020 - Child Language Disorders I: Birth to Five

CSD 6030 - Neuroscience of Communication

CSD 6120 - Child Language Disorders II: School-age Language and Literacy

CSD 6130 - Speech Sound Development and Disorders

CSD 6170 - Disorders of Fluency

CSD 6190 - Speech Language Pathology in Public Schools

CSD 6210 - Disorders of Phonation

CSD 6220 - Child Language Disorders III: School-age Psycholinguistic Perspectives

CSD 6230 - Diagnostic Procedures in Speech-Language Pathology

CSD 6240 - Neuromotor Disorders of Speech

CSD 6250 - Pediatric Feeding: Assessment and Intervention

CSD 6260 - Counseling and Interviewing in Communication Sciences and Disorders

CSD 6270 - Medical Aspects of Auditory Disorders

CSD 6290 - Adult Language Disorders

CSD 6340 - Clinical Methods in Speech-Language Pathology

CSD 6351 - Professional Education in Audiology I

CSD 6400 - Augmentative Communication

CSD 6410 - Dysphagia

CSD 6520 - Experimental Phonetics

CSD 6730 - Diagnostic Audiology

CSD 6731 - Advanced Diagnostic Audiology

CSD 6740 - Hearing Aids

CSD 6749 - Electrophysiologic Assessment

CSD 6750 - Electrophysiologic Assessment

CSD 6751 - Advanced Electrophysiologic Assessment

CSD 6770 - Advanced Hearing Science

CSD 6900 - Special Topics in Speech-Language Pathology

CSD 6901 - Special Topics in Speech-Language pathology

CSD 6902 - Special Topics in Speech-Language Pathology

CSD 6910 - Clinical Externship

CSD 6920 - Practicum in Diagnosis and Therapy

CSD 6921 - Audiology Practicum I