Genomic Data Science

Be a next generation sequencing data scientist.. Master the tools and techniques at the forefront of the sequencing data revolution.

Instructor: Mihaela Pertea, PhD , Steven Salzberg, PhD , Kasper Daniel Hansen, PhD , Jacob Pritt , Liliana Florea, PhD , Jeff Leek, PhD , Ben Langmead, PhD

Intermediate Level • 4 weeks to complete at 10 hours a week • Flexible Schedule

What You'll Learn

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

Skills You'll Gain

R Programming
Jupyter
Data Management
Statistical Methods
Linux Commands
Data Analysis Software
Statistical Analysis
Unix
Bioinformatics
Statistical Hypothesis Testing
Command-Line Interface
Data Structures

Shareable Certificate

Earn a shareable certificate to add to your LinkedIn profile

Outcomes

  • Learn in-demand skills from university and industry experts
  • Master a subject or tool with hands-on projects
  • Develop a deep understanding of key concepts
  • Earn a career certificate from Johns Hopkins University

6 courses series

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.

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.

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

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.

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.

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.

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