People Innovation Excellence

Predictive and Prescriptive Analytics

Learning Outcomes:

  1. Explain the fundamental concepts of descriptive, predictive, and prescriptive analytics, including the role of analytics in business decision-making processes.
  2. Apply data preparation and standard analytical methodologies (e.g., CRISP-DM, SEMMA) to explore and preprocess datasets for predictive modelling
  3. Analyze structured and unstructured data using classification, regression, forecasting, and optimization models, and interpret the results to support business insights.
  4. Analyze prescriptive analytics solutions using optimization and simulation models by integrating analytical results into the decision-making process.

Topics:

  1. Introduction to Business and Data Analytics
  2. Frameworks and Methodologies
  3. Data Preparation and Exploration
  4. Regression Analysis for Predictive Modelling
  5. Classification Algorithms
  6. Time Series Forecasting
  7. Case Base Reasoning
  8. Simulation Modeling for Decision Support
  9. Decision Analysis and Multi-Criteria Decision-Making (MCDM)
  10. The Future of Business Analytics

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