Course Search Results

  • DSA 5300: Analytical Methods & Opt

    3.00 Credits
    Pennsylvania Western University

    This course is an introduction to core quantitative methods for decision making. The course will cover optimization methods, Monte Carlo analysis, decision analysis, and methods to evaluate decisions ex post. The course will also introduce students to various scientific computing languages such as SAS,R, Python or other relevant tools.
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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 challenge due to exponential growth of data volume, velocity and variety. To cope up with this new demand, organizations are embracing new techniques like data visualization which involves data discovery and exploration. Technology giants like Amazon, Facebook, Google, Netflix use powerful data visualization tools to gain customer insights on their choices and apply them into their service offerings. Organizations are able to ask better questions and derive better decisions. This introductory course will teach students how organizations can harness the power of Big Data through data visualization. Students will learn how to capture data in visual format for better decisions using data viz tools like SAS, Tableau.
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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.
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