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Genomic Data Science

Kasper Daniel Hansen, PhD, Steven Salzberg, PhD, Jeff Leek, PhD, Liliana Florea, PhD, Ben Langmead, PhD, Jacob Pritt, James Taylor, PhD, and Mihaela Pertea, PhD

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What's inside

Six courses

Bioconductor for Genomic Data Science

(8 hours)

Learn to use Bioconductor tools for genomic data analysis. This course is part of the Genomic Big Data Specialization from Johns Hopkins University.

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Command Line Tools for Genomic Data Science

(11 hours)

Introduces the commands needed to manage and analyze directories, files, and large sets of genomic data.

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Algorithms for DNA Sequencing

We will learn computational methods for analyzing DNA sequencing data. We will learn about DNA, genomics, and how DNA sequencing is used. We will use Python to implement algorithms and data structures and to analyze real genomes and DNA sequencing datasets.

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Statistics for Genomic Data Science

An introduction to the statistics used in popular genomic data science projects.

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Introduction to Genomic Technologies

This course introduces the basic biology of modern genomics and the experimental tools used to measure it. We'll cover the Central Dogma of Molecular Biology and how next-generation sequencing can be used to measure DNA, RNA, and epigenetic patterns. You'll also get an introduction to the key concepts in computing and data science needed to understand how data from next-generation sequencing experiments are generated and analyzed.

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Python for Genomic Data Science

This class introduces the Python programming language and the iPython notebook.

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Time

1211 hours

Via

Coursera

Institution

Johns Hopkins University

Instructors

Kasper Daniel Hansen, PhD

Steven Salzberg, PhD

Jeff Leek, PhD

Liliana Florea, PhD

Ben Langmead, PhD

Jacob Pritt

James Taylor, PhD

Mihaela Pertea, PhD

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