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• DSA 5350: Machine Learning

  3.00 Credits

  Pennsylvania Western University

  
  Introduces machine learning (ML) concepts/algorithms. Covers basics of ML & how ML is used during interactions in students' everyday lives. Exposes students to ML through a programming framework/GUI application. ML is inherently mathematical, this course focuses on algorithms at a high level & being able to apply/compare them.
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• DSA 5400: Applied Data Mining

  3.00 Credits

  Pennsylvania Western University

  
  This course covers applied data mining methods on large data sets. Particular methods covered are principal components analysis, survival analysis, clustering, factor analysis, and other methods of dimension reduction. Data mining techniques of classification, prediction, reduction and exploration are discussed.
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• DSA 5500: App Pred Model & Anlytcs

  3.00 Credits

  Pennsylvania Western University

  
  This course provides both the concepts and practical applications of predictive analytics using data mining techniques of classification and prediction. Real business cases will be used to demonstrate the application of these data mining methods using tools such as SAS Enterprise Miner, XLMiner, Python or R.
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• DSA 5700: Big Data Analytics

  3.00 Credits

  Pennsylvania Western University

  
  This course covers methods to store and analyze large datasets ('Big Data'). Particular focus will be on Hadoop, and MapReduce technology. Further, the course covers No SQL, Key-value, concepts for handling unstructured data. There will be select topics for analytics on 'Big Data'. An integral part of this course is the application of database knowledge learned in the prior courses in the program. All data in this course will be stored in an appropriate relational (SQL) or document oriented (NoSQL) database. Students will then query the database for the data they will use in their analyses.
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• DSA 5800: Analytics Capstone

  3.00 Credits

  Pennsylvania Western University

  
  This course is an opportunity for students to apply the concepts, tools, and techniques learned during the Master's Program in Applied Data Analytics. In this course, students will take up real life data, explore and ask the right questions using the data, and derive insights to empower decision-making.
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• DSA 6100: Data Preparation and Cleaning

  3.00 Credits

  Pennsylvania Western University

  
  This course provides students with an introduction to the need for and methods for data cleaning. The course presents methods for locating and handling invalid values, out-of-range values, and missing values along with methods for managing datasets. The course uses SAS software.
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• DSA 6200: Data Visualization

  3.00 Credits

  Pennsylvania Western University

  
  Traditional Business Intelligence (BI) tools are unable to handle the Big Data challenges. Organizations are harnessing the power of Big Data through data visualization for quick understanding of trends and outliers. This course explores techniques and tools for visual analytics using SAS, Tableau and/or other tools.
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• DSA 6300: Big Data Tools

  3.00 Credits

  Pennsylvania Western University

  
  This course covers an introduction to big data analysis tools. The course provides an overview of SAS, Hadoop and other big data tools. The course covers the structure and framework of data analytic tools and covers the use of these tools to perform various analyses.
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• DSA 6400: Big Data Analytics

  3.00 Credits

  Pennsylvania Western University

  
  This course covers methods to store and analyze large datasets ('Big Data'). Particular focus will be on Hadoop, and MapReduce technology. Further, the course covers No SQL, Key-value, concepts for handling unstructured data. There will be select topics for analytics on 'Big Data'. An integral part of this course is the application of database knowledge learned in the prior courses in the program. All data in this course will be stored in an appropriate relational (SQL) or document oriented (NoSQL) database. Students will then query the database for the data they will use in their analyses. Prerequisite: DA 560.
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• DSA 6900: Data Sci & Anlytics Cap I

  3.00 Credits

  Pennsylvania Western University

  
  This capstone course gives students the opportunity to apply the SAS skills learned throughout the program using real-world data. Students shall demonstrate their competency in data science and analytics by integrating their knowledge in database and datawarehousing, data mining, predictive analytics, data visualization and big data analytics.
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