Predictive Modelling with R Training Course

Course Code

predmodr

Duration

14 hours (usually 2 days including breaks)

Requirements

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

Overview

R is an open-source free programming language for statistical computing, data analysis, and graphics. R is used by a growing number of managers and data analysts inside corporations and academia. R has a wide variety of packages for data mining.

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

Testimonials

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