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Course Criteria
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3.00 Credits
Examines the current curricula and methods of instruction used in middle and secondary level mathematics classrooms. Follows an investigative approach to middle-level and secondary mathematics instruction through hands-on activities that are standards based. Explores methods of teaching in diverse classrooms and teaching students with special needs.
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3.00 Credits
Applied statistics course in the analysis and forecasting of time series data. Linear time series regression models, ARIMA models, SARIMA models, GARCH models, and spectral theory are used to examine time series data. Emphasizes the applied aspects of these models. Computer software is used for data analysis.
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3.00 Credits
Covers acquiring, managing, and analyzing massive unstructured data through a project-driven approach. Includes theoretical analysis of clustering, visualization, link analysis, recommendation systems, mining social network graphs, dimensionality reduction with PCA and SVD, large-scale machine learning, neural nets and deep learning, distributed file systems, incremental data processing with Hadoop, NoSQL databases, cloud computing, and data security issues. Covers applications in web advertising, business, engineering, health care and social networks. Implements a computational project utilizing machine learning and artificial intelligence techniques.
Prerequisite:
( MATH 214 or MA 214 or MATH 216 or MA 216 or MATH 217 or MA 217 )
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3.00 Credits
Examines and develops expertise with sequences, patterns, and functions, including linear, quadratic, logarithmic, exponential, and trigonometric functions. Appropriate technology is incorporated. Explores curricular materials, resources, and activities relevant to teaching diverse groups at the elementary/middle level.
Prerequisite:
( MATH 152 or MA 152 )
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3.00 Credits
A study of set theory, real number system, functions, topology of Cartesian space, sequences, convergence and uniform convergence, continuity, and uniform continuity.
Prerequisite:
( MATH 124 or MA 124 ) ( MATH 272 or MA 272 )
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3.00 Credits
Includes the study of convergence sequences in Rn, global properties of continuity, uniform continuity, differentiation of Rn, Riemann integrals, and infinite series.
Prerequisite:
( MATH 421 or MA 421 )
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3.00 Credits
An introduction to the theory of functions of a complex variable. Topics included are elementary functions, analytic functions, conformal mapping, integration, series, and application.
Prerequisite:
( MATH 225 or MA 124 or MATH 227 or MA 227 )
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3.00 Credits
A study of sets, functions, continuity, compactness, the separation axioms, and metric spaces; application of topology to analysis is demonstrated.
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3.00 Credits
Provides insights into the teaching and learning of numbers and operations, algebra, geometry, measurement, probability, and statistics. Students become aware of and use the resources and methods of instruction for teaching mathematics at the secondary level. Must be taken within two semesters before student teaching.
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3.00 Credits
An introduction to using the basic tools of solving deterministic models in operations research. Includes optimization techniques and applications such as linear programming, nonlinear and dynamic programming, transportation models, and network models. In addition, sensitivity analysis, duality, simplex methods, and integer programming are discussed. Uses technology to solve problems and interpret the results.
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