Spécialisation Science des données génomiques

Commence le Apr 10

Spécialisation Science des données génomiques

Become a next generation sequencing data scientist

Master the tools and techniques at the forefront of the sequencing data revolution.

À propos de cette Spécialisation

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, Python, R, Bioconductor, and Galaxy. The sequence is a stand alone introduction to genomic data science or a perfect compliment to a primary degree or postdoc in biology, molecular biology, or genetics.

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courses
8 courses

Suivez l'ordre suggéré ou choisissez le vôtre.

projects
Projets

Conçu pour vous aider à vous exercer et à appliquer les compétences que vous avez acquises.

certificates
Certificats

Mettez en évidence vos nouvelles compétences sur votre CV ou sur LinkedIn.

Cours
Intermediate Specialization.
Some related experience required.
  1. COURS 1

    Introduction to Genomic Technologies

    Session à venir : Apr 10 — May 15.
    Sous-titres
    English

    À propos du cours

    This course introduces you to the basic biology of modern genomics and the experimental tools that we use to measure it. We'll introduce the Central Dogma of Molecular Biology and cover 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 that you'll need to understand how data from next-generation sequencing experiments are generated and analyzed. This is the first course in the Genomic Data Science Specialization.
  2. COURS 2

    Genomic Data Science with Galaxy

    Session à venir : Apr 10 — May 15.
    Sous-titres
    English

    À propos du cours

    Learn to use the tools that are available from the Galaxy Project. This is the second course in the Genomic Big Data Science Specialization.
  3. COURS 3

    Python for Genomic Data Science

    Session à venir : Apr 10 — May 15.
    Sous-titres
    English

    À propos du cours

    This class provides an introduction to the Python programming language and the iPython notebook. This is the third course in the Genomic Big Data Science Specialization from Johns Hopkins University.
  4. COURS 4

    Algorithmes pour le séquencage de l'ADN

    Session à venir : Apr 10 — May 15.
    Sous-titres
    English

    À propos du cours

    Nous étudierons des méthodes de calcul -- algorithmes et structures de données -- pour analyser les données de séquençage de l'ADN. Nous étudierons les bases de l'ADN et de la génomique, et comment le séquençage d'ADN est utilisé. Nous utiliserons Python pour mettre en place des algorithmes clés et des structures de données, et pour analyser des vrais jeux de données de séquençage de génomes et d'ADN.
  5. COURS 5

    Command Line Tools for Genomic Data Science

    Session à venir : Apr 10 — May 15.
    Sous-titres
    English

    À propos du cours

    Introduces to the commands that you need to manage and analyze directories, files, and large sets of genomic data. This is the fourth course in the Genomic Big Data Science Specialization from Johns Hopkins University.
  6. COURS 6

    Bioconductor for Genomic Data Science

    Session à venir : Apr 10 — May 15.
    Sous-titres
    English

    À propos du cours

    Learn to use tools from the Bioconductor project to perform analysis of genomic data. This is the fifth course in the Genomic Big Data Specialization from Johns Hopkins University.
  7. COURS 7

    Statistics for Genomic Data Science

    Session à venir : Apr 10 — May 15.
    Sous-titres
    English

    À propos du cours

    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.
  8. COURS 8

    Genomic Data Science Capstone

    Session à venir : May 22 — Aug 7.
    Engagement
    8 weeks of study, 2-4 hours/week
    Sous-titres
    English

    À propos du Projet Final

    In this culminating project, you will deploy the tools and techniques that you've mastered over the course of the specialization. You'll work with a real data set to perform analyses and prepare a report of your findings.

Créateurs

  • Université Johns-Hopkins

    Johns Hopkins University is recognized as a destination for excellent, ambitious scholars and a world leader in teaching and research. The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.

    The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.

  • Mihaela Pertea, PhD

    Mihaela Pertea, PhD

    Assistant Professor
  • Steven Salzberg, PhD

    Steven Salzberg, PhD

    Professor
  • Kasper Daniel Hansen, PhD

    Kasper Daniel Hansen, PhD

    Assistant Professor, Biostatistics and Genetic Medicine
  • Jacob Pritt

    Jacob Pritt

  • James Taylor, PhD

    James Taylor, PhD

    Associate Professor of Biology and Computer Science
  • Liliana Florea, PhD

    Liliana Florea, PhD

    Assistant Professor
  • Jeff Leek, PhD

    Jeff Leek, PhD

    Associate Professor, Biostatistics
  • Ben Langmead, PhD

    Ben Langmead, PhD

    Assistant Professor

FAQs

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