Coursera Specializations: Data Science, Systems Biology, Python Programming

January 22, 2014

(This article was first published on Getting Genetics Done, and kindly contributed to R-bloggers)

I first mentioned Coursera about a year ago, when I hired a new analyst in my core. This new hire came in as a very competent Python programmer with a molecular biology and microbial ecology background, but with very little experience in statistics. I got him to take Roger Peng’s Computing for Data Analysis course and Jeff Leek’s Data Analysis course, and four weeks later he was happily doing statistical analysis in R for gene expression experiments for several of our clients.

Today, Coursera announced Specializations – sequences of courses offered by the same institution, with the option of earning a specialization certificate from the University teaching the courses upon successful completion.

Among others, several specializations that look particularly interesting are:

Johns Hopkins University’s Data Science Specialization

This course, one of the longer specializations, is taught by Brian Caffo, Roger Peng, and Jeff Leek at Johns Hopkins. The courses in the specialization include:

  • The Data Scientist’s Toolbox
  • R Programming
  • Getting and Cleaning Data
  • Exploratory Data Analysis
  • Reproducible Research
  • Statistical Inference
  • Regression Models
  • Practical Machine Learning
  • Developing Data Products
  • A final Capstone Project
  • Systems Biology (Icahn School of Medicine at Mount Sainai)

    Courses include:

  • Introduction to Systems Biology
  • Network Analysis in Systems Biology
  • Dynamical Modeling Methods for Systems Biology
  • Integrated Analysis in Systems Biology
  • A final Capstone Project
  • Fundamentals of Computing (Rice University)

    Courses include:

  • An Introduction to Interactive Programming in Python
  • Principles of Computing
  • Algorithmic Thinking
  • A final Capstone Project
  • Check out the Coursera Specializations page for other Coursera series.

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