2025/2026
Time Series Analysis and Forecasting
Type:
Mago-Lego
Delivered by:
Big Data and Information Retrieval School
When:
2 module
Open to:
students of one campus
Language:
English
Contact hours:
24
Course Syllabus
Abstract
The course explores the principles and methodologies of time series analysis and forecasting, with a strong focus on practical applications in business contexts. Such topics as seasonality, trends, stationarity and autocorrelation, using business-oriented examples like demand forecasting, sales analysis and financial modeling will be covered. The course will introduce statistical and econometric models, including ARIMA and MSTL, and advanced machine learning approaches, including Prophet.A special emphasis will be placed on the use of external regressors - such as economic indicators, marketing activity and competitor data - to enhance model accuracy and incorporate real-world influences. Students will learn to integrate these regressors into their forecasting models, understanding their impact on business performance metrics and outcomes.