Genomic Data Science and Clustering (Bioinformatics V)
- Offered byCoursera
- Public/Government Institute
Genomic Data Science and Clustering (Bioinformatics V) at Coursera Overview
Genomic Data Science and Clustering (Bioinformatics V)
at Coursera
Duration | 10 hours |
Total fee | Free |
Mode of learning | Online |
Difficulty level | Intermediate |
Official Website | Explore Free Course  |
Credential | Certificate |
Genomic Data Science and Clustering (Bioinformatics V)
Table of content
- Overview
- Highlights
- Course Details
- Curriculum
Genomic Data Science and Clustering (Bioinformatics V) at Coursera Highlights
Genomic Data Science and Clustering (Bioinformatics V)
at Coursera
- Shareable Certificate Earn a Certificate upon completion
- 100% online Start instantly and learn at your own schedule.
- Course 5 of 7 in the Bioinformatics Specialization
- Flexible deadlines Reset deadlines in accordance to your schedule.
- Beginner Level
- Approx. 10 hours to complete
- English Subtitles: Arabic, French, Portuguese (European), Italian, Vietnamese, German, Russian, English, Spanish
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Genomic Data Science and Clustering (Bioinformatics V) at Coursera Course details
Genomic Data Science and Clustering (Bioinformatics V)
at Coursera
Skills you will learn
More about this course
- How do we infer which genes orchestrate various processes in the cell? How did humans migrate out of Africa and spread around the world? In this class, we will see that these two seemingly different questions can be addressed using similar algorithmic and machine learning techniques arising from the general problem of dividing data points into distinct clusters.
- In the first half of the course, we will introduce algorithms for clustering a group of objects into a collection of clusters based on their similarity, a classic problem in data science, and see how these algorithms can be applied to gene expression data.
- In the second half of the course, we will introduce another classic tool in data science called principal components analysis that can be used to preprocess multidimensional data before clustering in an effort to greatly reduce the number dimensions without losing much of the "signal" in the data.
- Finally, you will learn how to apply popular bioinformatics software tools to solve a real problem in clustering.
Genomic Data Science and Clustering (Bioinformatics V) at Coursera Curriculum
Genomic Data Science and Clustering (Bioinformatics V)
at Coursera
Week 1: Introduction to Clustering Algorithms
(Check Out Our Wacky Course Intro Video!)
Which Yeast Genes are Responsible for Wine Making?
Gene Expression Matrices
Clustering as an Optimization Problem
The Lloyd Algorithm for k-Means Clustering
Course Details
Week 1 FAQs (Optional)
Week 1 Quiz
Week 2: Advanced Clustering Techniques
From Hard to Soft Clustering
From Coin Flipping to k-Means Clustering
Expectation Maximization
Soft k-Means Clustering
Hierarchical Clustering
Week 2 FAQs (Optional)
Week 2 Quiz
Week 3: Introductory Algorithms in Population Genetics
Statement on This Week's Material
How Have Humans Populated the Earth?
Week 3 Quiz
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