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
HEADS UP!
This course is now part of The Complete Visual Guide to Machine Learning &Data Science, which combines all 4 Machine Learning courses from Maven Analytics. This course, along with the other individual courses in the series, will be retired soon.
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
PART2:Classification Modeling
PART3:Regression & Forecasting
PART4: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 SINGLELINEof code.
COURSEOUTLINE:
In this course, we’ll start by reviewing the Machine Learning landscape, exploring the differences between Supervised and Unsupervised Learning, and introducing several of the most common unsupervised techniques, including cluster analysis, association mining, outlier detection, and dimensionality reduction.
Throughout the course, we'll focus on breaking down each concept in plain and simple language to help you build an intuition for how these models actually work, from K-Means and Apriori to outlier detection, Principal Component Analysis, and more.
Section 1:Intro to Unsupervised Machine Learning
Unsupervised Learning Landscape
Common Unsupervised Techniques
Feature Engineering
The Unsupervised ML Workflow
Section 2:Clustering &Segmentation
Clustering Basics
K-Means Clustering
WSS &Elbow Plots
Hierarchical Clustering
Interpreting a Dendogram
Section 3:Association Mining
Association Mining Basics
The Apriori Algorithm
Basket Analysis
Minimum Support Thresholds
Infrequent &Multiple Item Sets
Markov Chains
Section 4:Outlier Detection
Outlier Detection Basics
Cross-Sectional Outliers
Nearest Neighbors
Time-Series Outliers
Residual Distribution
Section 5:Dimensionality Reduction
Dimensionality Reduction Basics
Principle Component Analysis (PCA)
Scree Plots
Advanced Techniques
Throughout the course, we'll introduce unique demos and real-world case studies to help solidify key concepts along the way.
You'll see how k-means can help identify customer segments, how apriori can be used for basket analysis and recommendation engines, and how outlier detection can spot anomalies in cross-sectional or time-series datasets.
If you’re ready to build the foundation for a successful career in Data Science, this is the course for you!
__________
Join todayand get immediate, lifetime accessto the following:
High-quality, on-demand video
Machine Learning:Unsupervised Learningebook
DownloadableExcel project file
ExpertQ&Aforum
30-day money-back guarantee
Happy learning!
-Josh M. (Lead Machine Learning Instructor, Maven Analytics)
__________
Looking for our full business intelligence stack? Search for "Maven Analytics"to browse our full course library, including Excel, Power BI, MySQL, andTableaucourses!
See why our courses are among the TOP-RATEDon Udemy:
"Some of the BESTcourses I've ever taken. I've studied several programming languages, Excel, VBA and web dev, and Maven is among the very best I've seen!" Russ C.
"This is my fourth course from Maven Analytics and my fourth 5-star review, so I'm running out of things to say. I wish Maven was in my life earlier!" Tatsiana M.
"Maven Analytics should become the new standard for all courses taught on Udemy!" Jonah M.
