Top Coursera Data Science Specializations: Comparison & Exclusive Insight

Johns Hopkins is a major player in the data science MOOC space, offering 3 specialization tracks though Coursera. Each specialization covers a particular approach to data science, and each is profiled below. You can see additional interview feedback from the programs' coordinator Jeff Leek further below.



Data Science Specialization, Johns Hopkins University

The Johns Hopkins' University's Data Science Specialization is the original flagship data science track offered by Coursera. Being offered in conjunction with SwiftKey and Yelp, this specialization centers on the R programming language and its ecosystem. The program promotes practicality yet has an academic slant as well, manifested in its emphasis on the reproducibility of data science research.

Containing the following 9 courses (plus capstone), it is also the most extensive offering available.

▪  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
▪  Data Science Capstone

Executive Data Science Specialization, Johns Hopkins University

Johns Hopkins' Executive Data Science Specialization is offered in conjunction with Zillow and DataCamp, and consists solely of one week courses. The specialization focuses on readying management for leveraging data science and interacting with data scientists, consisting of the following courses:

▪  A Crash Course in Data Science
▪  Building a Data Science Team
▪  Managing Data Analysis
▪  Data Science in Real Life
▪  Executive Data Science Capstone

Genomic Data Science Specialization, Johns Hopkins University

Johns Hopkins' Genomic Data Science Specialization is the first foray into a biological data science specialization for both Coursera and Johns Hopkins. The program focuses on using the command line, Python, R, Bioconductor, and Galaxy, and consists of these courses:

▪  Introduction to Genomic Technologies
▪  Genomic Data Science with Galaxy
▪  Python for Genomic Data Science
▪  Command Line Tools for Genomic Data Science
▪  Algorithms for DNA Sequencing
▪  Bioconductor for Genomic Data Science
▪  Statistics for Genomic Data Science
▪  Genomic Data Science Capstone

I was able to ask Johns Hopkins specializations coordinator Jeff Leek a few questions about the entirety of their data science tracks, and he provided the following insight.

What distinguishes your data science specialization from the others currently available via Coursera?

We currently offer 3 Specializations on Coursera: Data Science, Executive Data Science, and Genomic Data Science. These programs each have unique aspects:

Data Science - This is the first, most comprehensive (9 courses), largest (2 million+ enrollers, 1,000+ completers), and most science-driven data science Specialization on Coursera.

Executive Data Science - This is the only data science Specialization specifically designed for managers of data scientists. All the courses are designed to fit into a busy managers schedule (1 week courses) and all are on demand. We are also designing a cool interactive capstone experience with Zillow for this one.

Genomic Data Science - This is the only program covering Genomic Data Science on the Coursera platform. This is a major area of growth with interest in personalized medicine increasing by the day. The course covers the tools needed to understand and analyze data from next generation sequencing.

What 2 or 3 concepts or technologies does your specialization focus on the most?

Data Science - covers the spectrum of data science problems from Git/Github, to R, to specific tools/packages for data cleaning, inference, and machine learning. This course is largely R based since R is the most widely used language for data science in the wild.

Executive Data Science - covers a crash course in the basics of what data science is, how to build a data science team, and how to manage that team to success.

Genomic Data Science - covers an introduction to genomic technologies, python, Galaxy, R, the command line, Bioconductor, and statistics for genomics. This course is designed to get a person "up to speed" on doing genomic data science.

How does the specialization compare to similar course(s) at your university, if at all?

Parts of these courses are incorporated into programs in the Biostatistics (http://www.jhsph.edu/departments/biostatistics/), computer science (https://www.cs.jhu.edu/), biology (http://www.bio.jhu.edu/) and computational biology (https://ccb.jhu.edu/) programs at JHU. But these specializations were designed specifically for the MOOC platform to be available and fit into the schedules of people taking courses online.

What else would you like people to know about your specialization?

We are really excited about making classes available to the world and hope that they will be useful for people getting into a new field, transitioning careers, or looking for a job.