If you want to take advantage of the boom of interest in data science then you'll be interested in the series of Data Science courses from John Hopkins University that run on the Cousera Platform.

Earlier this year NSA let it be known that completion of this particular data science certificate program and others like it could be counted as the equivalent of one year's job experience by job applicants.

Where NSA leads other employers are likely to follow giving students extra motivation to embark on and successfully complete this particular credential.

A Coursera Specialization consists of a group of related courses and to achieve one you first have to earn a Verified Certificate for each of the courses included. The final stage in the Specialization is to complete a Capstone Project, which as the name suggest uses on the knowledge acquired throughout the series of courses and rounds it out with a substantial project. 

This specialization, which requires "some programming experience in any language" 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. This introductory video to the first module in the Specialization, The Data Scientist's Toolbox, sets the scene:

Like the other eight courses, the Data Scientists Toolbox is spread over four weeks but it has a lighter workload (1 - 4 hours per week compared to up to 9 hours per week) and a corresponding lower cost for joining the signature track $30 compared to $50. 

The road map for progressing towards the full Specialization is as follows:  

All of these courses currently begin at monthly intervals with the next starts for R Programming being July 6 and August 3.

The total duration of the program, including an 8-week Capstone project is around 40 weeks. All the courses included in the Data Science track can be studied standalone and for free if you are not interested in earning any credentials or doing the project.

The project details are:

• Build a predictive data model for analyzing large textual data sets
  
  
• Clean real-world data and perform complex regressions
  
  
• Create visualizations to communicate your data analyses
  
  
• Build a final data product in collaboration with SwiftKey, the company known for keyboard apps for smartphones

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