Forecast Modeling with Python for BI Analysts

Course overview

This training provides you with practical knowledge in the field of forecast modeling with Python. You will learn to categorize typical tasks confidently, apply suitable methods and tools, and prepare results in a comprehensible manner. The focus is on practical applications from the areas of Python, Data Science, AI, and Big Data that will support you in your role as a BI Analyst or in comparable professional tasks. Data preparation and time series structures in Python*Basics of time series data: trend components, seasonality, and noise*Data cleaning and indexing with pandas for forecasting purposes*Handling missing values, outliers, and data gaps in time series dataStatistical forecasting models and their application*Smoothing methods: exponential smoothing and Holt-Winters model*ARIMA and SARIMA models: parameter selection, estimation, and diagnostics*Model selection based on information criteria and error metricsMachine learning-based forecasting approaches*Regression and gradient boosting for forecasting applications*Feature engineering from time series data: lags, rolling statistics, calendar features*Validation strategies: walk-forward validation and cross-validation for time seriesDeployment and integration of forecasting models in the BI context*Model persistence and versioning with Python standard tools*Integration of forecasting models into BI dashboards and reporting pipelines*Monitoring model accuracy and automated retrainingThis training helps you to handle typical tasks in the field of forecast modeling with Python more confidently and efficiently. You will combine technical knowledge with practical methods and tools from the areas of Python, Data Science, AI, and Big Data. This strengthens your operational security for your role as a BI Analyst and allows you to apply the content directly in your professional life. The practical implementation is carried out with ChatGPT, Claude, Google Gemini, MS Copilot, Visual Studio Code, Jupyter Notebooks, and NumPy.

Upcoming dates

• 2026-08-30T22:00:00.000Z · 2026-12-20T23:00:00.000Z · Berlin · Blended Learning
• 2026-08-30T22:00:00.000Z · 2026-12-20T23:00:00.000Z · Erfurt · Blended Learning
• 2026-08-30T22:00:00.000Z · 2026-12-20T23:00:00.000Z · Augsburg, Bayern · Blended Learning
• 2026-08-30T22:00:00.000Z · 2026-12-20T23:00:00.000Z · Ludwigsburg, Württemberg · Blended Learning
• 2026-08-30T22:00:00.000Z · 2026-12-20T23:00:00.000Z · Freiburg im Breisgau · Blended Learning

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