Course Outline

Problems facing forecasters

  • Customer demand planning
  • Investor uncertainty
  • Economic planning
  • Seasonal changes in demand/utilization
  • Roles of risk and uncertainty

Time series Forecasting

  • Seasonal adjustment
  • Moving average
  • Exponential smoothing
  • Extrapolation
  • Linear prediction
  • Trend estimation
  • Stationarity and ARIMA modelling

Econometric methods (casual methods)

  • Regression analysis
  • Multiple linear regression
  • Multiple non-linear regression
  • Regression validation
  • Forecasting from regression

Judgemental methods

  • Surveys
  • Delphi method
  • Scenario building
  • Technology forecasting
  • Forecast by analogy

Simulation and other methods

  • Simulation
  • Prediction market
  • Probabilistic forecasting and Ensemble forecasting

Requirements

This course is part of the Data Scientist skill set (Domain: Analytical Techniques and Methods).

  14 Hours
 

Number of participants


Starts

Ends


Dates are subject to availability and take place between 09:30 and 16:30.
Open Training Courses require 5+ participants.

Testimonials (2)

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