Oklahoma State University

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CS 5423 Principles of Database Systems Prerequisites: CS 4343 and CS 4433 or equivalent, all with a grade of "C" or better. Description: An overview of database management systems, entity- relationship model, relational model, structural query language, relational algebra, functional dependencies, relational database design with normalization theorems, query processing, fault recovery, concurrent control, web-based database systems. Introduction to NoSQL databases, querying NoSQL databases. Credit hours: 3 Contact hours: Lecture: 3 Levels: Graduate Schedule types: Lecture Department/School: Computer Science CS 5433 Big Data Management Prerequisites: CS 5423 or CS 4433, with a grade of "C" or better. Description: Introduction to storing, processing and analyzing big data. Topics to be covered include map-reduce model within the Hadoop framework, data summarization, query and analysis; data munging and transformation; streaming data; transferring structured data; setting up distributed services; fast data processing using Apache Spark, including querying, live data streaming, machine learning and parallel processing; writing data pipeline jobs; introduction to machine learning using R or Python. Credit hours: 3 Contact hours: Lecture: 3 Levels: Graduate Schedule types: Lecture Department/School: Computer Science CS 5513 Numerical Computation Prerequisites: MATH 2233 with a grade of "C" or better; and MATH 3013 or MATH 3263 or equivalent courses with a grade of "C" or better; CS 3513 or MATH 4513 or an equivalent course with a grade of "C" or better; a knowledge of computer programming. Description: Errors in machine computation; condition of problems and stability of algorithms; interpolation and approximation; nonlinear equations; linear and nonlinear systems; differentiation and integration; applications to modeling, simulation, and/or optimization. Credit hours: 3 Contact hours: Lecture: 3 Levels: Graduate Schedule types: Lecture Department/School: Computer Science CS 5653 Automata and Finite State Machines Prerequisites: CS 5313 with a grade of "C" or better. Description: Sequential machines and automata. Hierarchy of recognizers. Decision problems and closure properties. Finite and infinite state machines. Cellular and stochastic automata. Coverings of automata. Credit hours: 3 Contact hours: Lecture: 3 Levels: Graduate Schedule types: Lecture Department/School: Computer Science

CS 5663 Computability and Decidability Prerequisites: CS 5313 with a grade of "C" or better.

Description: Primitive and partial recursive functions. Equivalence of models of computation. The Halting problem and undecidability. Reducing one problem to another or representation change. Tractability and the P-NP problem. Complexity hierarchies. Credit hours: 3 Contact hours: Lecture: 3 Levels: Graduate Schedule types: Lecture Department/School: Computer Science CS 5783 Machine Learning Prerequisites: CS 4343 and MATH 3013. Description: A probabilistic, statistical approach to automated pattern discovery applied to large datasets. Constructing computational models with this information and assessing their behavior and reliability. Representing data and devising tools for discovering these models. Class focuses on the development and analysis of learning algorithms as well as the mathematical formulations underlying statistical processing. Credit hours: 3 Contact hours: Lecture: 3 Levels: Graduate Schedule types: Lecture Department/School: Computer Science CS 5793 Artificial Intell II Prerequisites: CS 4793 with a grade of "C" or better. Description: Advance knowledge representation and expert system building, including reasoning under uncertainty. Applications to planning, intelligent agents, natural language processing, robotics, and machine learning. Credit hours: 3 Contact hours: Lecture: 3 Levels: Graduate Schedule types: Lecture Department/School: Computer Science CS 5813 Principles of Wireless Networks Prerequisites: CS 4283 or ECEN 4283, with a grade of "C" or better. Description: Wireless network operation, planning, mobility management, cellular and mobile data networks based on CDMA, TDMA, GSM, IEEE 802-11 WLANS, Adhoc networks, Bluetooth, power management, wireless geolocation and indoor positioning techniques. Same course as ECEN 5563. Credit hours: 3 Contact hours: Lecture: 3 Levels: Graduate Schedule types: Lecture Department/School: Computer Science CS 5823 Network Algorithmics Prerequisites: CS 4283 and CS 4323, with a grade of "C" or better. Description: Discusses principles of efficient network implementation- router architecture, end node architecture, data copying, timer maintenance, demultiplexing, forwarding table, lookups, switching, scheduling, IP traceback. Credit hours: 3 Contact hours: Lecture: 3 Levels: Graduate Schedule types: Lecture Department/School: Computer Science