Business Forecasting

What it is about

You will learn methods and tools for creating business forecasts and applying them. Topics include fundamentals of time series analysis, classical and modern modeling approaches (e.g., ARIMA, hierarchical forecasting, global models), machine-learning models (Random Forest, LGBM, XGBoost) as well as neural networks. By the end you will be able to select appropriate methods, compute forecasts with Python and the nixtla libraries, and present and justify the results.

What you will be able to do

• Understanding the importance of data analysis for business forecasting
• Knowledge of various forecasting techniques
• Selection and application of suitable forecasting procedures
• Application of Python and nixtla libraries to create forecasts
• Presentation and explanation of forecast results

What the module consists of

• Programmieraufgaben / Übungenpractical application of the methods with Python; verification of forecast calculations
• ProjektpräsentationIntroduction and discussion of a small forecasting project (results and methodology)

Teaching method

• Group workFosters collaboration on project and exercise tasks
• Programming with PythonImplementation of forecasting methods and practical practice
• PresentationsCommunication of results and justification of the approach
• ExercisesDeepening and application of the material