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Statistics for Genomic Data Science

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Free Online Course: Statistics for Genomic Data Science provided by Coursera is a comprehensive online course, which lasts for 4 weeks long, 9-10 hours worth of material. The course is taught in English and is free of charge. Upon completion of the course, you can receive an e-certificate from Coursera. Statistics for Genomic Data Science is taught by Jeff Leek.

Johns Hopkins University via Coursera
4 weeks long, 9-10 hours worth of material
Upcoming
Overview

  • An introduction to the statistics behind the most popular genomic data science projects. This is the sixth course in the Genomic Big Data Science Specialization from Johns Hopkins University.

Syllabus

    • Module 1
      • This course is structured to hit the key conceptual ideas of normalization, exploratory analysis, linear modeling, testing, and multiple testing that arise over and over in genomic studies.
    • Module 2
      • This week we will cover preprocessing, linear modeling, and batch effects.
    • Module 3
      • This week we will cover modeling non-continuous outcomes (like binary or count data), hypothesis testing, and multiple hypothesis testing.
    • Module 4
      • In this week we will cover a lot of the general pipelines people use to analyze specific data types like RNA-seq, GWAS, ChIP-Seq, and DNA Methylation studies.

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1.7, based on 3 Course votes at GetYourEducation
4.2, based on 326 Course reviews at Coursera

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