• MATH 4260: Intro to Stochastic Processes

  3.00 Credits

  Austin Peay State University

  
  Prerequisite: MATH 4240 or STAT 4240; Crosslisted: STAT 4260;Description: An introduction to stochastic processes and their applications: Poisson and compound Poisson processes; discrete and continuous time Markov chains; renewal theory; random walks and Brownian motion.
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• MATH 4270: Nonparametric Statistics

  3.00 Credits

  Austin Peay State University

  
  Prerequisite: MATH 4240;Description: Distribution free techniques for estimation of parameters and comparison of populations.
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• MATH 4280: Intro to Long Term Actua Math

  3.00 Credits

  Austin Peay State University

  
  Prerequisite: MATH/STAT 4240/5240 or Calculus-based probability at the level ofMATH/STAT 4240/5240 or Instructor Permission; Crosslisted: MATH 5240;Description: Prepares students for Long Term Actuarial Mathematics exam: Topicsinclude Long-term insurance coverages, Survival models and their estimation, Present Value Random Variables, Premium Calculation, Reserves and Pension Plans and Retirement Benefits.
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• MATH 4310: Machine Learning I

  3.00 Credits

  Austin Peay State University

  
  Prerequisite: MATH 1910 or instructor permission; Crosslisted: MATH 5310 & STAT 5310;Description: This course provides a broad introduction to machine learning andstatistical pattern recognition. Topics include: supervised learning (parametric/non-parametric learning, neural networks, support vector machines); unsupervised learning (clustering, dimensionality reduction, deep learning); learning theory and best practices for applying machine learning algorithms to areas including computer vision, text processing, and bioinformatics.
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• MATH 4320: Machine Learning II

  3.00 Credits

  Austin Peay State University

  
  Dual Listed: MATH 5320;Description: This course will assumes that the student is familiar with foundational machine learning concepts that include cost functions, gradient descent,backpropagation, and simple neural networks. Topics covered in thiscourse include deep neural networks, natural language processing,sentiment analysis, chatbots, recommender systems, and reinforcementlearning.
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• MATH 4321: Intro Sym Compu

  3.00 Credits

  Austin Peay State University

  
  Dual Listed: MATH 5321;Description: This course exposes students to computer algebra systems and other software packages. Students will learn to use these programs which will enhance their understanding in several courses in Mathematics, Statistics, Sciences and Engineering.
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• MATH 4400: Teaching Secondary Math

  3.00 Credits

  Austin Peay State University

  
  Prerequisite: Transition Point II and 19 hours in MATH major;Pre/Corequisite: MATH 3630;Description: Strategies for teaching high school mathematics that reflect best-practice recommendations. Field experience required.
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• MATH 4450: Intro to Mathematical Modeling

  3.00 Credits

  Austin Peay State University

  
  Prerequisite: MATH 1920, 3450;Description: Formation of mathematical models for problems in science and business. Special emphasis on models requiring algebra, calculus, discrete methods, and probabilistic models.
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• MATH 4460: Intro to Applied Mathematics

  3.00 Credits

  Austin Peay State University

  
  Prerequisite: MATH 2110, 3120, 3450 or permission of instructor;Description: Indepth study of an application of mathematics to industry, business, science or the social sciences. Specific topic chosen at the instructor's discretion. Possible topics include but are not limited to computational graph theory, stochastic, differential equations, financial mathematics, environmental mathematics, mathematical biology, data mining, etc. A project or paper is required.
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• MATH 4500: Introduction to Modern Algebra

  3.00 Credits

  Austin Peay State University

  
  Prerequisite: MATH 3010 with a grade of C or higher or permission of instructor;Description: Relations, maps, abstract algebras, groups, rings, integral domains, order, morphisms, fields, and factorization.
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