Learn how to use Power BI for series exponential smoothing and handle errors using advanced Power Query techniques

Visualise series data in Power BI

Apply and manipulate series exponential smoothing forecast

Transform unstructured data into series data

Understand series theory, and the concepts of seasonal and cyclical data

Handle series forecasting errors using advanced techniques in Power Query

Compare actual values versus forecast values

A prior, basic understanding and usage of Power BI is recommended

Prior experience using Power Query or writing M scripts is useful but not required

An interest in stock trading is appreciated but not required

Have Power BI desktop and Microsoft Excel installed

By understanding how series exponential smoothing works, students will be able to manipulate the forecast line efficiently for daily, monthly and yearly predictions of univariate data.

As part of the course, students will gain hands-on experience in advanced error handling techniques in Power Query and be able to tune parameters efficiently for cyclical and seasonal datasets.

Business analysts interested in series analysis

Finance professionals curious about Power BI and trend analysis

Python developers curious about Power BI and trend analysis

Power BI and Excel users interested in trend analysis

Business professionals curious about Power BI, forecasting and series analysis



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