Course Search Results

• DATA 6480: Data Mining

  3.00 Credits

  Utah State University

  
  This course introduces data mining and business intelligence technologies. Students utilize a clustering algorithm for customer segmentation, an association rule algorithm for cross-selling/website optimization, single and ensemble classifiers for churn prediction/fraud detection/targeted ads, and visualization tools for data and output representation. Additional coursework is required for those enrolled in the graduate-level course.
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• DATA 6490: Prescriptive Analytics and Management Science

  3.00 Credits

  Utah State University

  
  This course introduces the concepts, basic theories, and skills to make quantitatively supported decisions using management science, mathematical programming and optimization tools. Additional coursework is required for those enrolled in the graduate-level course.
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• DATA 6500: Advanced Python Programming for Analytics

  3.00 Credits

  Utah State University

  
  This course covers advanced Python programming principles and analytics applications, including object-oriented programming, sorting, data structures, cloud computing, data mining, and introductory machine learning. Additional coursework is required for those enrolled in the graduate-level course.
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• DATA 6570: Building Software With Artificial Intelligence

  3.00 Credits

  Utah State University

  
  AI-generated code, and associated tools, are rapidly advancing. This course covers software engineering principles, architecture principles, software development with AI-generated code, AI code testing, and AI code deployment of a larger software applications. Additional coursework is required for those enrolled in the graduate-level course.
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• DATA 6580: Machine Learning Operations

  3.00 Credits

  Utah State University

  
  This hands-on course develops proficiency in deploying, versioning, and monitoring machine learning models in a production environment. Students directly build and implement models and their key components, ensuring they are fully functional and prepared for use in making predictions. Additional coursework is required for those enrolled in the graduate-level course.
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• DATA 6610: Advanced Machine Learning for Analytics

  3.00 Credits

  Utah State University

  
  This course covers applications of modern machine learning for business decision-making. Students learn about the modeling process to enable rational data-driven business decisions, using machine learning algorithms and their computational implementation in real-world settings. Additional coursework is required for those enrolled in the graduate-level course.
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• DATA 6620: Advanced Regression for Causal Inference

  3.00 Credits

  Utah State University

  
  This course focuses on the application of regression to inform decision-making, particularly using interpretable models to understand the effect of interventions on business outcomes. Students learn to model experimental and observational data and infer causality instead of correlation only. Additional coursework is required for those enrolled in the graduate-level course.
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• DATA 6630: Deep Forecasting

  3.00 Credits

  Utah State University

  
  This course explores time series prediction using Python to build classical, machine learning, and deep learning models. Through coding projects, students develop cutting-edge skills in analyzing complex data, programming predictive models, and applying techniques to real-world problems. Additional coursework is required for those enrolled in the graduate-level course.
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• DATA 6690: Computational Methods for FinTech

  3.00 Credits

  Utah State University

  
  Computational finance is an interdisciplinary pillar of modern FinTech, at the intersection of data science, computer science, and economics. In this course students apply tools from computational science and statistics to identify and exploit arbitrage opportunities for entrepreneurial financial innovation. Additional coursework is required for those enrolled in the graduate-level course.
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• DATA 6695: Predictive Methods for FinTech

  3.00 Credits

  Utah State University

  
  Prediction is a core activity of modern FinTech. This course uses probability, computational statistics, machine learning, and financial econometrics to develop and implement predictive strategies for trading and risk management by identifying and exploiting arbitrage opportunities. Additional coursework is required for those enrolled in the graduate-level course.
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