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Goliath Research Academy
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Unsupervised Learning: Cluster Analysis with Python

The course comprehensively covers the fundamentals and advanced techniques of clustering, from foundational algorithms like k-Means to sophisticated density-based methods such as OPTICS and DBSCAN, utilizing Python and Jupyter Notebooks for practical implementations. It culminates in practical applications through a hands-on project to master the art of uncovering hidden structures in data.
7 minutes

Video Time

26 minutes

Ebooks Time

2 (no grades)

Quizzes

8

Notebooks

1 (15 questions)

Exam

1

Certificate

David Izada-Rodriguez

Computer Scientist, Software Engineer, Instructor
About me
After years of researching and teaching Computer Science, I switched to its applications to several industries. This experience allowed me to develop general-purpose techniques to be used from the factory floor to enterprise applications on the cloud. As I did at the beginning of my career, I am ready to share my experience.

Gladys Casas-Cardoso

Data Scientist, Statistician, Instructor
About me
I am a Mathematics and Computer Sciences professor since 1994. With a master's degree in Mathematics and a Ph.D. in Technical Sciences, I enjoy teaching at all levels and ages.
I look forward to sharing my love of building meaningful and compelling content with all students to develop their data analysis abilities.
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