Find patterns in data and predict future outcomes with Power BI. Learn regression, clustering, and forecasting techniques to transform historical information into insights that drive smarter business decisions.
Overview
Syllabus
- Introduction to Predictive Data Analytics
- This lesson will introduce predictive analytics concepts and a general overview of when to use it in your organization. We will also review the project and the primary tool we will use: Power BI.
- Regression
- We will review one Machine Learning technique that involves numeric data: Regression. We will learn about its main features, how to interpret it and how to construct it using Power BI.
- Classification and Clustering
- We will learn additional ML techniques: Classification and Clustering. We will review its main features, some clustering techniques, how to interpret them and how to construct clusters with Power BI.
- Time-Series Forecasting
- We will review what a time-series is. Also, we will review deterministic and probabilistic forecasting methods, how to read and interpret time-series and how to create forecasts using Power BI.
- Additional Tools and Techniques
- We will review additional ML and AI-powered tools using Power BI: we will focus on Power BI dataflows and its AutoML features and use two AI-powered visuals: the Q&A and the smart narratives.
- Commercial Flight Analysis in the State of New York
- In this project, students will use the data of past flights departing from the State of New York to analyze and give recommendations about flight delays.
- Microsoft Power BI Workspace
- In this lesson, you'll learn how to set up a Windows desktop workspace to use Power BI
Taught by
Daniel Roca