MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + .srt | Duration: 14 lectures (1h 19m) | Size: 459 MB
In this course, students will learn about the forecasting models available in Power BI.
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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