AI Demand Forecasting
About This Course
This course provides a structured and practice-oriented introduction to demand forecasting within engineering and operational contexts. It covers the end-to-end analytics lifecycle, from defining business and process requirements to statistical data analysis, algorithmic model development, performance evaluation, and integration into operational forecasting workflows.
Designed for data analysts, planners, and engineers, the course develops competencies in interpreting demand data using statistical techniques and applying algorithmic and artificial intelligence (AI) models to support engineering and operational decision-making. Participants will work with realistic datasets and use case scenarios to analyse trends and patterns, evaluate forecasting performance, and translate analytical insights into process improvement opportunities.
By the end of the course, participants will be equipped to integrate AI-driven forecasting solutions into engineering processes, interpret statistical outputs responsibly, and support data-informed operational planning and continuous improvement initiatives.
What You'll Learn
- Analyse engineering and operational requirements to define AI-driven demand forecasting problems, including clarifying forecast scope, time horizon, decision objectives, and operational impact.
- Preprocess and analyse demand data using statistical techniques to identify trends, seasonality, variability, and data quality issues that influence forecasting performance.
- Apply statistical and AI models in demand forecasting, including selecting and implementing suitable baseline and advanced models based on demand behaviour and business needs.
- Evaluate forecasting performance using statistical metrics and operational indicators, assessing accuracy, bias, robustness, and suitability for deployment.
- Develop and assess hybrid forecasting approaches using different model types on the FusionCast platform, comparing performance and understanding the benefits of model integration.
- Interpret AI-driven forecasting outputs to support engineering and operational decisions, translating analytical results into actionable planning and optimisation insights.
Entry Requirements
Min. Diploma