A MOOC-by-MOOC Big Data Immersion Plan

So you're looking to wet your feet with Big Data. You want to understand what it is, get a firm grasp on the current technology, and know how it can help you or your company. How do you start and what is the most accelerated way to accomplish this goal?

With IBM Predicting a 28 percent rise in employment relating to Big Data, you are going to have to come to grips that it's just not a passing fad. Companies are waking up to the fact that employees proficient in using Big Data to solve business problems are increasingly valuable, whatever their background or position in an organization.

A lot of this is because of the ease of self-service infrastructure and tools designed to automate many of the technical but repetitive tasks involved with Big Data: data cleaning, preparation, and analytics. This means workers are increasingly able to carry out complex, data-driven operations such as predictive modeling and automation without getting their hands dirty coding complex algorithms from scratch.

There are a plethora of ways to learn how to do Big Data. My recommendation is MOOCs (Massive Open Online Courses). These courses are simple to complete, easy to understand and inexpensive. One of the best places to start is MOOC List where you can find a complete list of free online courses and MOOCs.

Here is the path I recommend for gaining those valuable Big Data skills.

Select your site

One of the best course sites I have dealt with is Coursera. It's easy to navigate and has a TON of course offerings from leading schools, including many Ivy League institutions. Just log on the site, register for free and pick and pay for the courses you want to take.

There are other sites good sites as well, but Coursera is by far my favorite, especially for Big Data. You can even earn a Big Data degree: There are bachelor's, master's and even doctorate-level degrees available in varying Big Data topics.

Picking your first course

It's not my nature to slowly begin any new courses; I like to jump in with both feet and really take it to the next level with learning. Just as jumping into a pool enables me to get used to the water sooner, so too does jumping into a new course. You know yourself better than I do, of course, so whatever method works for you is fine.

For my first course, I chose "The Data Scientist's Toolbox." This four-week course, taught by a distinguished professor at Johns Hopkins University, covered everything from the "R" programming language to huge data sets that you can import and develop against. GITHUB is another useful source of large data sets that you can use after you get setup with the "R" Programming tools.

Moving along

The University of San Diego offers a solid trifecta of courses: "Introduction to Big Data," "Big Data," and "Big Data Modeling." I recommend these for your next set of courses. Access will set you back $50 a month, and you will need a couple of months to complete these courses, but the value is there.

These courses are taught by USD's Chief Data Science Officer and will give you a full taste of what is out there for Big Data, but in easily digestible, bite-size chunks.

Your next step

Also available from the University of San Diego — one of the Top 10 public universities in the United States, incidentally — is a "Hadoop Platform and Application Framework" course. I strongly recommend this be your next big data course.

Hadoop is the application or storage structure application that houses Big Data. Your online learning education just won't be complete if you didn't learn the application and support of what "holds" big data. It's a really important step to take in your education — don't skip it.

Machine learning and beyond

Synonymous with big data is Machine Learning, where computers obtain an almost magical quality of AI. This emerging technology always impresses me; I love learning about it. Coursera has a "Google Cloud Platform Big Data and Machine Learning Fundamentals" course, a great item to include in your Big Data toolbox. Definitely get a taste of this topic, it will be very useful.

Throw a fun one in

All work and no play makes Jack a dull boy, so if your brain is feeling overloaded, then take a break from hardcore learning and turn to something fun like "Big Data, Genes, and Medicine" offered by The State University of New York. The course description is a bit long, but it does tell you all you need to know:

"This course distills for you expert knowledge and skills mastered by professionals in Health Big Data Science and Bioinformatics. You will learn exciting facts about the human body biology and chemistry, genetics, and medicine that will be intertwined with the science of Big Data and skills to harness the avalanche of data openly available at your fingertips and which we are just starting to make sense of.

"We'll investigate the different steps required to master Big Data analytics on real datasets, including Next Generation Sequencing data, in a healthcare and biological context, from preparing data for analysis to completing the analysis, interpreting the results, visualizing them, and sharing the results."

Take this one to give yourself a break ... sorta.

Platforms

Most the cloud platforms currently operating have Big Data built in. Amazon and Azure both have Big Data tools built into their offerings and online training classes have responded. You can take an Azure "Data Lake Class" or anything on Amazon's host of products. A quick perusal of Big Data on AWS will give you a vast array of applications for you to specialize in.

Tying it all together

What would Big Data be without visualization? Just a pile of data. My choice for visualizing Big Data is Tableau Software. To learn about it, simply take "Data Visualization with Tableau" offered by the University of California, Davis. This will get you a satisfying snoot-full of Tableau visualizations.

I can't praise the visualization power of this course enough. It does the most important thing connected to Big Data — helps you interpret and present it to decision makers. Remember, if you can't show the data to anyone in a nice, pretty and understandable manner, then you have failed.

Other Options

While I prefer Coursera, it isn't the only MOOC game in town. Two solid options are Udemy and Lynda. Another MOOC site that ranks high with users is edX.org. It has a ton of resources available, along with a lot of free classes. If you want to make a career change, this is a good place to start. Figure on a 1-to-3 year ramp up, depending on how adept you are at learning.

There really is no end to the amount of online learning available, and new courses are being offered every day. The advantage of these courses is that they can be taken at a time convenient for people with hectic schedules. You will appreciate the ability to learn in your pajamas. Or when you don't feel like doing anything else for work, just grab a beer and take the course of your choice.

Have fun

Keep in mind that if you get bored with a class, you can stop. Stopping is always better than quitting. If a course bores you, go on to another one. Try talking to others who are taking the class. You can establish a buddy system where you take classes with your friends or coworkers.

The best thing about learning online is that it all gets done how YOU want it to get done. With MOOCs only two things matter: that you are learning what you want to learn, and that you are having fun doing so.