From Forecasting to Prescriptive analytics

13:30-17:00, January 26 @ Foyer 1

Workshop / Overview

How can we translate forecasts into optimal decisions? While predictive analytics employs mathematical methodologies (econometrics, machine learning) to analyze data and forecast future events, prescriptive analytics exploits optimization methodologies to identify the best course of action to achieve a goal.

In this workshop, we will:

  1. translate business goals into KPIs,
  2. translate business requirements and constraints into proper mathematical form and
  3. employ optimization algorithms on forecasted results to build an optimal schedule that improves the KPIs.

Workshop / Outcome

Familiarize yourself with important optimization concepts, especially Linear Programming ad Mixed Integer Programming; learn how to formulate optimization models; gain hands-on experience with mathematical optimization frameworks in Python. After the workshop the participant will be able to tackle a broad spectrum problems in the area of prescriptive analytics.

Workshop / Difficulty

Intermediate level

Workshop / Prerequisites

  • Basic Python programming knowledge
  • Some proficiency in mathematics
  • Own laptop with latest Anaconda installed
  • Conda environment created based on the file Opt_AMLD2020.yml (run the command “conda env create –f Opt_AMLD2020.yml”)

Track / Co-organizers

Sotirios Dimopoulos

Manager Data & Analytics, KPMG Switzerland

Niccolò Moretti

Assistant Manager, KPMG

Kostja Siefen

Technical Account Manager, Gurobi Optimization

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AMLD / Global partners