Unsupervised Machine Learning

International Business Machines Corporation, or IBM, is a renowned technology company based in the United States. As a leader in driving technological advancement, IBM offers opportunities for you to be part of a community that focuses on innovation and research. You will have access to a company that has been at the forefront of technological development for over a century, with a strong presence in cloud computing, artificial intelligence, and cybersecurity.

Specifically, IBM focuses on delivering enterprise solutions in areas like cloud computing, artificial intelligence, cybersecurity, and quantum computing. With 345 programs available, you can explore different aspects of technology and consulting services. For instance, IBM's AI platform Watson has revolutionized data analytics and machine learning, giving you a unique opportunity to learn from industry leaders.

As you join IBM, you will be part of a global network with a strong presence in the United States. You will have opportunities to engage with a company that holds thousands of patents and is committed to addressing global challenges through technology. With its headquarters in Armonk, New York, you will be close to a major hub for business and technology, offering a unique blend of academic and professional experiences.

The Unsupervised Machine Learning course is a non-degree program that focuses on one of the main types of machine learning. It's taught in English and helps you find insights from data sets without a target or labeled variable. You'll learn clustering and dimension reduction algorithms for unsupervised learning.

This course covers hands-on practices for unsupervised learning, including selecting the best algorithm for your data. You'll learn to explain the kinds of problems suitable for unsupervised learning approaches, the curse of dimensionality, and common clustering and dimensionality-reduction algorithms.

After completing this course, you can pursue roles like data scientist, business analyst, or data engineer. You'll have the skills to work with unsupervised machine learning techniques in a business setting, and be able to explain metrics relevant for characterizing clusters and try clustering points where appropriate.