Introduction to Clustering and PCA
Enhance your skills in dimensionality reduction and finding patterns in data through this Introduction to Clustering and PCA course. Learn about unsupervised learning, clustering, and principal component analysis in detail.
Skills you’ll Learn
About this Course
This free course will familiarize you with principal component analysis and clustering fundamentals. These two methods are crucial components of Data Science and Machine Learning. You will first get introduced to clustering and learn to use it to group data points together or find patterns in data. Further, you will acquire a thorough understanding of principal component analysis, and you will understand its process and know the significance and impact it has. Lastly, you will learn how PCA aids in dimensionality reduction with some examples. Enroll and complete the modules and a quiz at the end of this course to gain a free certificate of course completion.
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Course Outline
This module starts by introducing you to unsupervised learning. Next, you will learn about clustering and go through its applications.
In this module, you will learn from scratch about principal component analysis, and you will comprehend its significance and the impact it has. You will also go through its process and understand the principal component analysis with respect to signal to noise ratio.
This module familiarizes you with the effective technique called PCA, in which you can bring out the composite way of reducing dimensionality without losing crucial data. You will also learn it better through some examples.
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Frequently Asked Questions
What prerequisites are required to learn this Introduction to Clustering and PCA course?
This is a beginner-friendly course where you don’t need any specific prerequisites and start learning from scratch.
How long does it take to complete this free Introduction to Clustering and PCA course?
This free Introduction to Clustering and PCA course contains an hour of self-paced videos.
What are my next learning options after this Introduction to Clustering and PCA course?
You can enroll in MIT’s Data Science and Machine Learning Course offered by Great Learning.
Is it worth learning principal component analysis and clustering?
Principal component analysis and clustering are crucial methods for data analysis with many uses. Finding patterns in data and conducting data analysis can benefit significantly from these two strategies. Although they can be utilized independently, they are frequently combined to get a more comprehensive picture of the data. As a result, it is worth learning both methods.
Will I have lifetime access to the free course?
Yes. Once you enroll in this course, you have lifetime access to it, allowing you to learn anytime and anywhere.