Analytics for Decision Making

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.

Course 1: Introduction to Predictive Modeling
- Offered by University of Minnesota. Welcome to Introduction to Predictive Modeling, the first course in the University of Minnesota’s ... Enroll for free.

Course 2: Optimization for Decision Making
- Offered by University of Minnesota. In this data-driven world, companies are often interested in knowing what is the "best" course of ... Enroll for free.

Course 3: Advanced Models for Decision Making
- Offered by University of Minnesota. Business analysts need to be able to prescribe optimal solution to problems. But analytics courses are ... Enroll for free.

Course 4: Simulation Models for Decision Making
- Offered by University of Minnesota. This course is primarily aimed at third- and fourth-year undergraduate students or graduate students ... Enroll for free.