As I’m beginning to take my career into a new direction, I realize that I have a lot to learn.

I know math and basic statistics, but I need to know how to clean data,  how to present it so businesses can use it to make decisions,  and how to work with statistical programming languages.

I’m still trying to figure out if analysis or database administration is the better path for me, but to do that, I need more understanding of what is involved in each path.

In the last year, some of what I’ve really enjoyed doing was figuring out how to get information out of a database. That’s why I started studying SQL.

In my current position, I need to present information from varying sources (Google Analytics, Facebook Insights, other social media advertising and posting info, internal databases of customers, etc) in ways the company can use to make important decisions.

I started researching obtaining a Master’s degree or university extension certificate in Data Science, but the cost is beyond my capability for now.

When I heard that veterans can get a verified certificate through Coursera, I researched what was available.

The Johns Hopkins Data Science Specialization sequence seemed to be similar to the university extension certifications I was researching.

Each course in the sequence is 4 weeks long. Each course has video lectures, most with either PDF and/or HTML slides, a quiz each week, and programming projects.

So far, I’ve taken two courses in this sequence.

The Data Science Toolkit is an overview of the sequence, with an emphasis on getting the basic programs and accounts setup. It has you install R (an open source statistical programming language), RStudio (a more user-friendly interface for R) and Git (a version control program) as well as set up an account at GitHub.

GitHub is pretty interesting. It’s a place where you can share programmers share and crowdsource their software projects and documentation. I was unaware of this tool before the class. I’m looking forward to using it more.

R Programming is a brief, very brief, introduction to some of R’s capabilities.

Included in this course is a study “package” called swirl. This was probably the most useful part of the course – and was counted as extra credit.

The lectures seemed to prepare a person for the quizzes, but were really inadequate for the programming assignments, especially if you’re a novice programmer. There were many discussions on the forums for the course about this.

I found that I did ok with swirl and a little outside the course research, but I downloaded all the course material and want to walk through the programming assignments again on my own time.

Getting and Cleaning Data starts this week.

I’ll be adding the verified certificates to my LinkedIn profile as I receive them.

• coursera
• data science
• learning