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Genomic Data Science and Clustering (Bioinformatics V)

This course is part of Bioinformatics Specialization.

This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Bioinformatics Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.

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پښتو, বাংলা, اردو, 3 more

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Genomic Data Science and Clustering (Bioinformatics V)

This course includes

9 Hours

Of Self-paced video lessons

Intermediate Level

Completion Certificate

awarded on course completion

Free course

What you'll learn

  • Master clustering algorithms for genomic data analysis

  • Apply machine learning to gene expression data

  • Understand dimensionality reduction techniques

  • Implement hierarchical and k-means clustering

  • Analyze population genetics using data science methods

Skills you'll gain

Data Clustering
Machine Learning
Genomic Analysis
Bioinformatics
K-means Clustering
Gene Expression Analysis
Principal Component Analysis
Population Genetics
Algorithm Design
Data Science

This course includes:

1.1 Hours PreRecorded video

3 quizzes

Access on Mobile, Tablet, Desktop

FullTime access

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There are 3 modules in this course

This course explores advanced data science techniques for analyzing genomic data, focusing on clustering algorithms and dimensionality reduction. Students learn to apply machine learning methods to analyze gene expression data and study population genetics. The curriculum covers both theoretical foundations and practical applications of clustering techniques, including k-means clustering, hierarchical clustering, and principal components analysis.

Introduction to Clustering Algorithms

Module 1 · 4 Hours to complete

Advanced Clustering Techniques

Module 2 · 4 Hours to complete

Introductory Algorithms in Population Genetics

Module 3 · 50 Minutes to complete

Fee Structure

Individual course purchase is not available - to enroll in this course with a certificate, you need to purchase the complete Professional Certificate Course. For enrollment and detailed fee structure, visit the following: Bioinformatics Specialization

Instructors

Pavel Pevzner
Pavel Pevzner

8,33,777 Students

16 Courses

Pioneering Bioinformatics Scholar and Computational Biology Innovator

Pavel Arkadevich Pevzner serves as the Ronald R. Taylor Professor of Computer Science at the University of California, San Diego, and director of the NIH Center for Computational Mass Spectrometry, where he has revolutionized the field of computational biology since 2000. After receiving his Ph.D. in mathematics and physics from the Moscow Institute of Physics and Technology, he completed postdoctoral work with Michael Waterman at USC, before establishing himself through positions at Penn State and USC. His groundbreaking research spans bioinformatics algorithms, genome rearrangements, DNA sequencing, and computational proteomics, leading to significant advances in genome assembly and antibiotics discovery. His academic excellence has been recognized through numerous prestigious honors, including the Howard Hughes Medical Institute Professorship (2006), ACM Fellowship (2010), ISCB Fellowship (2012), and the ACM Paris Kanellakis Theory and Practice Award (2018). As an educator, he has transformed bioinformatics education through innovative approaches, including the development of massive open online courses that have reached over half a million students, and authored influential textbooks including "Computational Molecular Biology: An Algorithmic Approach" and "Bioinformatics Algorithms: An Active Learning Approach"

Phillip Compeau
Phillip Compeau

4.1 rating

282 Reviews

2,88,261 Students

8 Courses

Computational Biology Educator and Educational Innovation Pioneer

Phillip Compeau is an Assistant Teaching Professor in the Carnegie Mellon University Computational Biology Department, where he serves as Assistant Director of the Master's in Computational Biology program. He holds a Ph.D. in mathematics from UC San Diego and completed his Master's degree at Cambridge University. Phillip co-founded Rosalind, an online platform for learning bioinformatics. A retired tennis player, he dreams of one day going pro in golf.

Genomic Data Science and Clustering (Bioinformatics V)

This course includes

9 Hours

Of Self-paced video lessons

Intermediate Level

Completion Certificate

awarded on course completion

Free course

Testimonials

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Frequently asked questions

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