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Find out how you can give end users the capability to explore AI and machine learning in Power BI.
Overview
Syllabus
Introduction
- The power of Power BI
- What you should know
- Overviewing AI and machine learning types
- Defining dimensionality
- Utilizing the Power BI ecosystem and Azure
- Configuring R in Power BI Desktop
- Introducing the course project
- Utilizing AI in the ETL framework
- Configuring parameters
- Analyzing dataset statistics and distributions
- Configuring separate error logs for existing datasets
- Running Vision algorithms
- Utilizing Text Analytics algorithms
- Leveraging AI and the star schema
- Adjusting DateTime fields for lags
- Configuring aggregations and dimensionality
- Filtering options
- Calculating DAX measures
- Challenge: Single variable
- Calculating rolling averages
- Utilizing binning to create histograms
- Summarizing statistics
- Splitting a category with small multiples
- Leveraging violin plots
- Solution: Single variable
- Visualizing relationships with scatter plots
- Accessing the Analytics pane
- Calculating correlations
- Visualizing correlations
- Adding clustering to existing visuals
- Calculating best fit line
- Utilizing the outlier detection visual
- Calculating outliers
- Contextualizing outliers
- Challenge: Multiple variables
- Solution: Multiple variables
- Determining key drivers with decomposition tree visual
- Leveraging the Q&A visual
- Utilizing parameters to model what-if scenarios
- Discovering key insights with the Key Influencer visual
- Challenge: AI visuals
- Solution: AI visuals
- Organizing time series analysis
- Adding forecasting from the Analytics pane
- Leveraging anomaly detection
- Utilizing ARIMA forecasting
- Incorporating seasonality through TBATS forecasting
- Analyzing predictions vs. actuals
- Challenge: Time series analysis
- Solution: Time series analysis
- Designing a consolidated view for sharing
- Uploading and sharing in the Power BI service
- Configuring quick insights
- Challenge: Shared view
- Solution: Shared view
- How to learn ML and AI in Power BI
Taught by
Helen Wall
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Reviews
1.0 rating, based on 1 Class Central review
4.6 rating at LinkedIn Learning based on 708 ratings
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Helen Wall (the instructor) gives a very contrived and odd presentation. Much of the content could have been transmitted much more efficiently by text, or at least with a text-based summary. I got halfway through before giving up and I still hadn't learned anything substantive.
However, the real problem is that neither Helen, nor the course description, give any indication that the course requires a organization account. (A personal account on Microsoft Fabric will not give you access to Dataflows and other crucial features needed to complete the course.) It would have been very nice to know this several hours ago.
