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About This Path

The path starts with "Machine Learning Models in Power BI", which introduces you to the realm of predictive analytics within the Power BI environment. By mastering data preprocessing and the nuances of model creation, you'll be equipped to make insightful forecasts. The course also accentuates the power of Pycaret, an AutoML library, enabling you to optimize regression models.

Transitioning to "Python I for Power BI Users", Gaelim Holland demystifies the Python language, emphasizing its compatibility and synergy with Power BI. After laying down a solid foundation by setting up Python in a clean environment, the course ventures into Python's capabilities, from data transformations to high-level statistical analyses. By the end, you'll have the tools and knowledge to blend Power BI's visualization capabilities with Python's analytical power, forging a formidable data analysis toolkit.

Who Should Take This Path

  • Data Analysts: Professionals aiming to meld the predictive capabilities of machine learning with their Power BI expertise
  • Business Intelligence Enthusiasts: Individuals keen on enhancing their BI dashboards with Python-driven insights
  • Power BI Aficionados: Users eager to dive deep into advanced Power BI functionalities, leveraging Python and machine learning
  • Students & Academics: Individuals from business, statistics, or computer science backgrounds, aiming to acquire a practical skillset
  • Decision Makers: Leaders looking to drive strategic choices through enriched Power BI reports, augmented by Python and predictive analytics

What Are The Path Requirements

  •  A foundational grasp of data analysis concepts and familiarity with the Power BI environment
  •  While prior machine learning experience isn't mandatory, a basic understanding of statistical methods can be beneficial
  • Access to Power BI and a functional computer setup for practical exercises
  • An eagerness to explore and master the synergy between Power BI, Python, and machine learning

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