Statistics for Genomic Data Science

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.

About The Course

It isn't enough to just know how to use the tools. Doing genomic data science well means understanding the statistical principles at work. This class will provide an introduction to the statistics behind the most popular genomic data science projects. This will help you ask better questions, plan better research, and interpret the results more accurately.

Frequently Asked Questions

  • Do I need any special materials to take this course? 
No, you only need a computer.
  • What is the workload in this course?
No more than 2 hours of video lectures, a weekly quiz with no more than 10 questions. This class will also require extra time by the student to open and practice using Python.

Recommended Background

Prerequisite: Introduction to Sequencing Technologies
Very strongly recommended: R programming is essentially a prerequisite for this course since Bioconductor builds on R programming. We don't require an R Programming certificate to enter this course, but you will need the skills and knowledge covered in R Programming to do well in this course. If you don't have those skills already, you should expect to struggle in this course.

The target audience of this course are individuals in the molecular or computational sciences who want how to learn how to perform basic computational biology. This class is “hands on” and designed to get you started with the tools you need to perform Genomic Data Science.