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(This article was first published on <strong><a href="http://blog.revolutionanalytics.com/2017/07/harvardx.html"> Revolutions</a></strong>, and kindly contributed to <a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers)</a> </div>
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<p>Rafael Irizarry from the Harvard T.H. Chan School of Public Health has presented a number of courses on R and Biostatistics on EdX, and he recently also <a rel="nofollow" href="http://rafalab.github.io/pages/harvardx.html" target="_blank">provided an index</a> of all of the course modules as YouTube videos with supplemental materials. The EdX courses are linked below, which you can take for free, or simply follow the series of YouTube videos and materials provided in the index. </p>
<p><a rel="nofollow" href="https://leanpub.com/dataanalysisforthelifesciences" target="_blank"><img alt="DALS" title="DALS" src="http://revolution-computing.typepad.com/.a/6a010534b1db25970b01b8d29797b0970c-120wi"></a><strong><a rel="nofollow" href="https://www.edx.org/xseries/data-analysis-life-sciences" target="_blank">Data Analysis for the Life Sciences Series</a></strong> </p>
<ul>
<li><a rel="nofollow" href="https://www.edx.org/course/statistics-r-harvardx-ph525-1x-0" target="_blank">Statistics and R</a></li>
<li><a rel="nofollow" href="https://www.edx.org/course/introduction-linear-models-matrix-harvardx-ph525-2x-1" target="_blank">Introduction to Linear Models and Matrix Algebra</a></li>
<li><a rel="nofollow" href="https://www.edx.org/course/statistical-inference-modeling-high-harvardx-ph525-3x-0" target="_blank">Statistical Interference and Modeling for High-throughput Experiments</a></li>
<li><a rel="nofollow" href="https://www.edx.org/course/high-dimensional-data-analysis-harvardx-ph525-4x-0" target="_blank">High-Dimensional Data Analysis</a></li>
</ul>
<p>A <a rel="nofollow" href="https://leanpub.com/dataanalysisforthelifesciences" target="_blank">companion book</a> and associated <a rel="nofollow" href="http://genomicsclass.github.io/book/" target="_blank">R Markdown documents</a> are also available for download.</p>
<p><strong>Genomics Data Analysis Series</strong></p>
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<li><a rel="nofollow" href="https://www.edx.org/course/introduction-bioconductor-annotation-harvardx-ph525-5x-0" target="_blank">Introduction to Bioconductor: Annotation and Analysis of Genomes and Genomic Assays</a></li>
<li><a rel="nofollow" href="https://www.edx.org/course/high-performance-computing-reproducible-harvardx-ph525-6x-0" target="_blank">High-performance computing for reproducible genomics with Bioconductor</a></li>
<li><a rel="nofollow" href="https://www.edx.org/course/case-studies-functional-genomics-harvardx-ph525-7x-0" target="_blank">Case Studies in Functional Genomics</a></li>
</ul>
<p>For links to all of the course components, including videos and supplementary materials, follow the link below.</p>
<p>rafalab: <a rel="nofollow" href="http://rafalab.github.io/pages/harvardx.html" target="_blank">HarvardX Biomedical Data Science Open Online Training</a></p>
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<div>To <strong>leave a comment</strong> for the author, please follow the link and comment on their blog: <strong><a href="http://blog.revolutionanalytics.com/2017/07/harvardx.html"> Revolutions</a></strong>.</div>
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