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Unsupervised Learning


Learn how to distill messy data into meaningful groups with unsupervised machine learning! By the end of this course, you’ll know how to perform cluster analyses and dimensionality reduction using Python’s powerful machine-learning package, scikit-learn.

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  • Estimated time
    15 hours

  • Enroll by
    October 12, 2022

    Get access to classroom immediately on enrollment

  • Prerequisites
    Intermediate Python, basic understanding of Machine Learning and Supervised Learning concepts

What You Will Learn

  1. Unsupervised Learning

    21 hours to complete

    Unsupervised learning gives you the power to find common patterns within data without knowing what to look for, and its application is virtually limitless — from market segmentation to computer vision to fraud detection. In this course, you’ll learn a multitude of techniques, including hierarchical and density-based clustering, gaussian mixture models, cluster validation, principal component analysis (PCA), and independent component analysis (ICA). In addition, you’ll apply what you’ve learned to identify customer segments within complex demographic data for a mail-order sales company.

    Prerequisite knowledge

    1. Clustering

      Learn the basics of clustering data and cluster data with the K-means algorithm.

      • Hierarchical and Density-Based Clustering

        Cluster data with Single Linkage Clustering and DBSCAN, a clustering method that captures the insight that clusters are dense group of points.

        • Gaussian Mixture Models

          Cluster data with Gaussian Mixture Models and optimize Gaussian Mixture Models with Expectation Maximization.

          • Dimensionality Reduction

            Reduce the dimensionality of the data using Principal Component Analysis and Independent Component Analysis.

            • Course Project: Creating Customer Segments

              In this project, you will apply unsupervised learning techniques on product spending data collected for customers of a wholesale distributor in Lisbon, Portugal to identify customer segments hidden in the data.


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            All our programs include:

            • Real-world projects from industry experts

              With real-world projects and immersive content built in partnership with top-tier companies, you’ll master the tech skills companies want.

            • Technical mentor support

              Our knowledgeable mentors guide your learning and are focused on answering your questions, motivating you, and keeping you on track.

            • Workspaces

              Validate your understanding of concepts learned by checking the output and quality of your code in real-time.

            • Flexible learning program

              Tailor a learning plan that fits your busy life. Learn at your own pace and reach your personal goals on the schedule that works best for you.

            Course offerings

            • Class content

              • Real-world projects
              • Project reviews
              • Project feedback from experienced reviewers
            • Student services

              • Technical mentor support
              • Student community

            Succeed with personalized services.

            We provide services customized for your needs at every step of your learning journey to ensure your success.

            Get timely feedback on your projects.

            • Personalized feedback
            • Unlimited submissions and feedback loops
            • Practical tips and industry best practices
            • Additional suggested resources to improve
            • 1,400+

              project reviewers

            • 2.7M

              projects reviewed

            • 88/100

              reviewer rating

            • 1.1 hours

              avg project review turnaround time

            Mentors available to answer your questions.

            • Support for all your technical questions
            • Questions answered quickly by our team of technical mentors
            • 1,400+

              technical mentors

            • 0.85 hours

              median response time

            Learn with the best.

            Learn with the best.

            • Josh Bernhard

              Data Scientist at Nerd Wallet

              Josh has been sharing his passion for data for nearly a decade at all levels of university, and as Lead Data Science Instructor at Galvanize. He's used data science for work ranging from cancer research to process automation.

            • Jay Alammar


              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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            Unsupervised Learning

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