Genomic Data Science Specialization

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About Course

Genomic Data Science Specialization, With genomics sparks a revolution in medical discoveries, it becomes imperative to be able to better understand the genome, and be able to leverage the data and information from genomic datasets. Genomic Data Science is the field that applies statistics and data science to the genome. This Specialization covers the concepts and tools to understand, analyze, and interpret data from next generation sequencing experiments. It teaches the most common tools used in genomic data science including how to use the command line, along with a variety of software implementation tools like Python, R, and Bioconductor. This Specialization is designed to serve as both a standalone introduction to genomic data science or as a perfect compliment to a primary degree or postdoc in biology, molecular biology, or genetics, for scientists in these fields seeking to gain familiarity in data science and statistical tools to better interact with the data in their everyday work.

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What Will You Learn?

  • Next generation sequencing experiments
  • Genomic technologies
  • DNA, RNA and epigenetic patterns
  • Genome analysis

Course Content

01. Introduction to Genomic Technologies

  • 001 01_syllabus_instructions.html
    00:00
  • 003 02_pre-course-survey_instructions.html
    00:00
  • 007 03_why-genomics.mp4
    00:00
  • 011 04_what-is-genomics.mp4
    00:00
  • 015 05_what-is-genomic-data-science.mp4
    00:00
  • 019 01_just-enough-cell-biology.mp4
    00:00
  • 023 02_important-molecules-in-molecular-biology.mp4
    00:00
  • 027 03_the-human-genome-project.mp4
    00:00
  • 031 04_molecular-biology-structures.mp4
    00:00
  • 035 05_from-genes-to-phenotypes.mp4
    00:00
  • 040 01_polymerase-chain-reaction.mp4
    00:00
  • 044 02_next-generation-sequencing.mp4
    00:00
  • 048 03_applications-of-sequencing.mp4
    00:00
  • 053 01_what-is-computer-science.mp4
    00:00
  • 057 02_algorithms.mp4
    00:00
  • 061 03_memory-and-data-structures.mp4
    00:00
  • 065 04_efficiency.mp4
    00:00
  • 069 05_software-engineering.mp4
    00:00
  • 073 06_what-is-computational-biology-software.mp4
    00:00
  • 078 01_why-care-about-statistics.mp4
    00:00
  • 082 02_what-went-wrong.mp4
    00:00
  • 086 03_the-central-dogma-of-statistics.mp4
    00:00
  • 090 04_data-sharing-plans.mp4
    00:00
  • 094 05_getting-help-with-statistics.mp4
    00:00
  • 098 06_plotting-your-data.mp4
    00:00
  • 102 07_sample-size-and-variability.mp4
    00:00
  • 106 08_statistical-significance.mp4
    00:00
  • 110 09_multiple-testing.mp4
    00:00
  • 114 10_study-design-batch-effects-and-confounding.mp4
    00:00
  • 115 01_quiz-4-data-science-technology_exam.html
    00:00
  • 119 02_course-project_exam.html
    00:00
  • 120 01_post-course-survey_instructions.html
    00:00
  • links.txt
    00:00

02. Python for Genomic Data Science

03. Algorithms for DNA Sequencing

04. Command Line Tools for Genomic Data Science

05. Bioconductor for Genomic Data Science

06. Statistics for Genomic Data Science

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