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Unsupervised Learning

Course

In this course, you'll learn how to apply unsupervised learning to solve real-world problems.

In this course, you'll learn how to apply unsupervised learning to solve real-world problems.

Intermediate

3 weeks

Real-world Projects

Completion Certificate

Last Updated May 19, 2024

Skills you'll learn:

Gaussian mixture models • Single linkage clustering • K-means clustering • Dimensionality reduction

Prerequisites:

Intermediate Python • Basic descriptive statistics • Basic probability

Course Lessons

Lesson 1

Clustering

Clustering is one of the most common methods of unsupervised learning. Here, we'll discuss the K-means clustering algorithm.

Lesson 2

Hierarchical and Density Based Clustering

We continue to look at clustering methods. Here, we'll discuss hierarchical clustering and density-based clustering (DBSCAN).

Lesson 3

Gaussian Mixture Models and Cluster Validation

In this lesson, we discuss Gaussian mixture model clustering. We then talk about the cluster analysis process and how to validate clustering results.

Lesson 4

Dimensionality Reduction and PCA

Often we need to reduce a large number of features in our data to a smaller, more relevant set. Principal Component Analysis, or PCA, is a method of feature extraction and dimensionality reduction.

Lesson 5

Random Projection and ICA

In this lesson, we will look at two other methods for feature extraction and dimensionality reduction: Random Projection and Independent Component Analysis (ICA).

Lesson 6 • Project

Project: Identify Customer Segments

In this project, you'll apply your unsupervised learning skills to two demographics datasets, to identify segments and clusters in the population, and see how customers of a company map to them.

Taught By The Best

Photo of Josh Bernhard

Josh Bernhard

Staff Data Scientist

Josh has been sharing his passion for data for over a decade. He's used data science for work ranging from cancer research to process automation. He recently has found a passion for solving data science problems within marketplace companies.

Photo of Jay Alammar

Jay Alammar

Instructor

Jay is a software engineer, the founder of Qaym (an Arabic-language review site), and the Investment Principal at STV, a $500 million venture capital fund focused on high-technology startups.

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Projects are based on real-world scenarios and challenges, allowing you to apply the skills you learn to practical situations, while giving you real hands-on experience.

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4 Months

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Average time to complete a Nanodegree program

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