Analytics for Decision Making
half-circle
vector

Analytics for Decision Making

Highlights

The field of analytics is typically built on four pillars: Descriptive Analytics, Predictive Analytics, Causal Analytics, and Prescriptive Analytics. Descriptive analytics (e.g., visualization, BI) deal with the exploration of data for patterns, predictive analytics (e.g., data mining, time-series forecasting) identifies what can happen next, causal modeling establishes causation, and prescriptive analytics help with formulating decisions. This specialization focuses on the Prescriptive Analytics (the final pillar). This specialization will review basic predictive modeling techniques that can be used to estimate values of relevant parameters, and then use optimization and simulation techniques to formulate decisions based on these parameter values and situational constraints. The specialization will teach how to model and solve decision-making problems using predictive models, linear optimization, and simulation methods.

About the Course Provider

Coursera provides access to more than 3000+ courses across a wide variety of subjects in parntership with different universities and organizations.

Course by

  • self
    Self paced
  • domain
    Domain Data Science & AI
  • subs
    Monthly Subscription
    Course is included in
    1. Starter @ AED 99 + VAT
    2. Professional @ AED 149 + VAT
  • fee
    Buy Now Option not available
  • language
    Language English