data mining 27

  • Define data mining as an enabling technology for business analytics and understand the objectives and benefits of data mining.
  • Become familiar with the wide range of applications of data mining Learn the standardized data mining processes Learn different methods and algorithms of data mining
  • Build awareness of the existing data mining software tools Understand the privacy issues, pitfalls, and myths of data mining
  • Describe text analytics and understand the need for text mining
  • Differentiate among text analytics, text mining, and data mining and the application areas for text mining
  • Know the process of carrying out a text mining project
  • Describe sentiment analysis
  • Develop familiarity with popular applications of sentiment analysis Learn the common methods for sentiment analysis Become familiar with speech analytics as it relates to sentiment analysis
  • Understand the applications of prescriptive analytics techniques
  • Understand the basic concepts of analytical decision modeling and understand the concepts of analytical models for selected decision problems
  • Describe how spreadsheets can be used for analytical modeling and solutions Explain the basic concepts of optimization and when to use them
  • Explain what is meant by sensitivity analysis, what-if analysis, and goal seeking Understand the concepts and applications of different types of simulation and understand potential applications of discrete event simulation
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