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Course Outline
Key Challenges for Forecasters
- Planning for customer demand
- Managing investor uncertainty
- Strategic economic planning
- Addressing seasonal fluctuations in demand and utilization
- Understanding the roles of risk and uncertainty
Time Series Forecasting Techniques
- Seasonal adjustment methods
- Moving average approaches
- Exponential smoothing
- Extrapolation techniques
- Linear prediction models
- Trend estimation
- Analyzing stationarity and ARIMA modeling
Econometric Methods (Causal Approaches)
- Regression analysis
- Multiple linear regression
- Multiple non-linear regression
- Validation of regression models
- Generating forecasts from regression results
Judgemental Forecasting Methods
- Conducting surveys
- The Delphi method
- Scenario building
- Technology forecasting
- Forecasting by analogy
Simulation and Other Approaches
- Simulation techniques
- Prediction markets
- Probabilistic and Ensemble forecasting
Requirements
This course is included within the Data Scientist skill set, specifically under the domain of Analytical Techniques and Methods.
14 Hours
Testimonials (2)
The exercises.
Elena Velkova - CEED Bulgaria
Course - Predictive Modelling with R
He was very informative and helpful.
