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Machine Learning for BI, PART 3 Regression & Forecasting

Machine Learning for BI, PART 3: Regression & Forecasting

Demystify Machine Learning and build foundational Data Science skills like regression & forecasting, without any code!

This course is PART 3 of a 4-PART SERIES designed to help you build a strong, foundational understanding of Machine Learning. This course makes data science approachable to everyday people, and is designed to demystify powerful Machine Learning tools & techniques without trying to teach you a coding language at the same time. Instead, we’ll use familiar, user-friendly tools like Microsoft Excel to break down complex topics and help you understand exactly HOW and WHY machine learning works before you dive into programming languages like Python or R. Unlike most Data Science and Machine Learning courses, you won’t write a SINGLE LINE of code.

What you’ll learn

  • Build foundational machine learning & data science skills, without writing complex code
  • Use intuitive, user-friendly tools like Microsoft Excel to introduce & demystify machine learning tools & techniques
  • Predict numerical outcomes using regression modeling and time-series forecasting techniques
  • Calculate diagnostic metrics like R-Squared, Mean Error, F-Significance and P-Values to diagnose model quality
  • Explore unique, hands-on case studies to see how regression analysis can be applied to real-world business intelligence use cases

You May Also Need This Course

Machine Learning for BI, PART 2: Classification Modeling

Machine Learning for BI, PART 4: Unsupervised Learning

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