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Start 4 June 2026 18:50

Einde 4 June 2026

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Data Science in Power BI Desktop - Achieving AI Analytics

Explore advanced data science techniques for custom visuals in Power BI, enhancing your ability to create AI-driven analytics and insightful visualizations.
PASS Data Community Summit via YouTube

PASS Data Community Summit

6076 Cursussen


57 minutes

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Overzicht

Explore advanced data science techniques for custom visuals in Power BI, enhancing your ability to create AI-driven analytics and insightful visualizations.

Lesprogramma

  • Introduction to Data Science in Power BI
  • Overview of Power BI Desktop
    Introduction to AI and Data Science Concepts
    Importance of AI Analytics in Business Intelligence
  • Power BI Desktop Advanced Features
  • Data Import and Transformation
    Utilization of DAX for advanced calculations
    Creating sophisticated data models
  • Developing Custom Visuals
  • Introduction to R and Python scripting in Power BI
    Designing and deploying custom visuals
    Leveraging R and Python libraries for data visualization
  • AI Insights with Power BI
  • Utilizing AI visuals in Power BI
    Integrating Azure AI and Cognitive Services
    Building predictive models within Power BI
  • Enhancing Analytics with Machine Learning
  • Introduction to Machine Learning concepts
    Implementing machine learning models using Python in Power BI
    Applying models to create predictive analytics
  • Interactive and Insightful Dashboards
  • Designing interactive dashboards with custom visuals
    Enhancing user experience with AI-driven analytics
    Sharing and collaborating on insights
  • Real-World Applications and Case Studies
  • Industry-specific applications of AI in Power BI
    Case studies showcasing successful implementation of AI analytics
  • Best Practices and Future Trends
  • Data governance and ethical considerations in AI analytics
    Future trends in AI and data science for Power BI
  • Capstone Project
  • Develop a comprehensive Power BI report utilizing AI elements
    Presentation and peer review of the project outputs

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