Johns Hopkins University has partnered with Coursera to offer free high-quality universally available online education designed and led by Johns Hopkins professors. Coursera offers many courses that are of interest to data scientists and researchers meeting the challenge of Big Data. IDIES Member at Large Roger Peng, Associate Director Steven Salzberg, and IDIES Affiliates Jeffrey Leek, Kasper Daniel Hansen, Ben Langmead, and James Taylor are active Coursera instructors.

Specializations

Coursera currently offers two specializations of interest to researchers interested in data-intensive science. A Coursera Specialization is a series of courses culminating in a capstone project. Courses must be taken on the identity-verified fee-based Signature Track to count towards a Specialization.

Data Science Specialization

Students completing this program have a solid foundation in all aspects of Data Science. This specialization covers the concepts and tools you’ll need throughout the entire data science pipeline, from asking the right kinds of questions to making inferences and publishing results. Coursera offers a Data Science Specialization (fee-based) that includes the courses listed below and others.

The Data Scientist’s Toolbox:
The fundamentals of identifying, approaching, and solving data science problems.
 
Statistical Inference:
The basics of understanding data with statistics. In this course the students learn how to draw inferences from data using statistical models, and from those inferences, how to select the best method of analysis.
 
R Programming:
Learn R, the programming language of choice for data scientists and data miners.
 

Genomic Data Science

Students completing this program will be able to understand, analyze, and interpret data from next-generation sequencing experiments. You will learn common tools of genomic data science. The Genomic Data Science Specialization includes a series of courses culminating in a capstone project. Although all courses in the Specialization can be taken at no cost, they must be taken on the identity-verified fee-based Signature Track to count towards the Genomic Data Science Specialization.

The Genomic Data Science Specialization (fee-based) includes the following courses, many of which are taught by IDIES Affiliates.

Introduction to Genomic Technologies:
The basic biology of modern genomics and the experimental tools used for measurement.
 
Genomic Data Science with Galaxy:
Learn to use the tools that are available from the Galaxy Project.
 
Python for Genomic Data Science:
An introduction to the Python programming language and the iPython notebook.
 
Algorithms for DNA Sequencing:
Computational methods for analyzing DNA sequencing data.
 
Bioconductor for Genomic Data Science:
Learn to use tools from the Bioconductor project to perform analysis of genomic data.
 
Statistics for Genomic Data Science::
An introduction to the statistics behind the most popular genomic data science projects.
 
Command Line Tools for Genomic Data Science:
The commands that you need to manage and analyze directories, files, and large sets of genomic data.