Machine Learning for BI, PART 4: Unsupervised Learning
Learn powerful Unsupervised Machine Learning techniques like clustering, association mining, outlier detection and more!
This course is PART 4 of a 4-PART SERIES designed to help you build a strong, foundational understanding of Machine Learning:
- PART 1: QA & Data Profiling
- PART 2: Classification
- PART 3: Regression & Forecasting
- PART 4: Unsupervised 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
- Explore powerful techniques for clustering, association mining, outlier detection, and dimensionality reduction
- Learn how ML models like K-Means, Apriori, Markov and Principal Component Analysis actually work
- Enjoy unique, hands-on demos to see how Unsupervised ML can be applied to real-world Business Intelligence projects
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