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MATH 4400: Stat Analy of Big & Small Data
3.00 Credits
Weber State University
This course combines and develops the knowledge and skills used in big and small data using both theory and application. The course deals with methods to analyze data with varying volume, velocity, and variety and their associated challenges. Topics such as data mining, predictive analytics, heteroskedasticity of data, and data visualization will be explored.
Prerequisite:
CS 1400 and CS 2550 and MATH 1040 and MATH 1160 and MATH 1220 and MATH 1220 and MATH 3410
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MATH 4610: Numerical Analysis I
3.00 Credits
Weber State University
Introduction to numerical methods. Use of the digital computer in solving otherwise intractable problems.
Prerequisite:
MATH 2270
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MATH 4620: Numerical Analysis II
3.00 Credits
Weber State University
A continuation of MATH 4610 - Introduction to numerical methods. Use of the digital computer in solving otherwise intractable problems.
Prerequisite:
MATH 4610
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MATH 4710: Partial Differential Equations
3.00 Credits
Weber State University
Partial differential equations. First and second order equations, characteristics and classifications, methods of solution, applications. Prerequisite: MATH 3710.
Prerequisite:
MATH 3710
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MATH 4750: Topics In Mathematics
2.00 - 4.00 Credits
Weber State University
This course will vary with the demand and may be taken more than once for a maximum of 8 credit hours. Prerequisite: Consent of the instructor.
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MATH 4910: Senior Research Project
3.00 Credits
Weber State University
Mathematical research project for seniors. Students may not register for this course the last semester before they intend to graduate. Prerequisite: Instructor approval.
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MATH 4920: Workshop
1.00 - 4.00 Credits
Weber State University
Consult the semester class schedule for the current offering under this number. The specific title and credit authorized will appear on the student transcript.
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MATH 4925: Problems, Journals, & Research
1.00 Credits
Weber State University
Development and demonstration of independent learning and communication skills through advanced problems solving, presenting journal articles, or undergraduate research under guidance of an advisor.
Prerequisite:
MATH 2925
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MATH 6400: Advanced Statistical Learning
3.00 Credits
Weber State University
Students will learn about Statistical Learning and Data Science which are so widely used in the technology sector and beyond. You will learn about common statistical methods and algorithms used by Amazon, Facebook, and Google to made predictive models for data. This course will have an emphasis on modeling (numeric and non numeric) data, model selection, and neural networks.
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MATH 6450: Applied Stats & Regression
3.00 Credits
Weber State University
Students learn the knowledge and skills necessary for applied statistical analysis. These methods allow focus typically on a selection of advanced regression analysis, missing data, categorical data analysis, time series in relation to regression, colinear data, and model and variable selection. This course also focuses on Applied Statistics & Regression in the context of both a statistical and data scientist view point as this course is part of the Masters of Data Science.
Prerequisite:
CS 3580 and MATH 3410 and MATH 3450
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