IT pros looking to add big data skills to their career toolkit can benefit from online learning opportunities, often without breaking the bank.
1. A-B-L: Always Be Learning
If the salesperson's mantra is Always Be Closing, modern IT pros should adopt and adapt it for their own career: Always Be Learning.
If the salesperson's mantra is Always Be Closing, modern IT pros should adopt and adapt it for their own career: Always Be Learning.
If you're not learning, you're frozen in IT time. The technology world has always been one of change, but the pace and frequency of that change has never been greater. The last couple of decades have featured wave after wave of new technologies and their often disruptive effects, not just on lifestyles and business models but on job descriptions, career paths, IT organizational charts, and even IT budget and decision-making power. And there's little sympathy for the IT pros in the middle of all this Change with a capital C.
How do you ensure you're not just maintaining but capitalizing on this rapid-fire change? A-B-L: Always Be Learning.
Consider the expanding, evolving world of big data, which occupies an interesting place in today's IT landscape: It's both a significant driver of this aforementioned world of change, and also a significant product of it, a result of recent, sweeping shifts in IT like mobility and cloud.
Big data, as both a cause and effect of technological change, is impacting your career, whether you realize it or not. Even if you're not actively seeking a big data role, massive amounts of information -- and massive business interest in that information -- is affecting IT. Marketing departments have more say in technology acquisitions and decisions, CEOs want insights (and typically don't want to hear about the IT challenges impeding the speedy delivery of those insights), and meanwhile aging infrastructure and applications wheeze under the weight of these new and increasing demands. More such change is on its way, too: the Internet of Things (IoT), as a prime example, will fuel continued change and continued data growth in the not-so-distant future.
Like many explosive -- and, yes, trendy -- technology developments, big data has also spawned its own industry within an industry. That industry is hiring and it pays well, by the way.
Back to that whole learning thing: Big data is definitely creating tremendous opportunities for the IT pros that know and understand it. That could be in a new role such as a data engineer or simply in a revision of an existing job description -- one that makes you more versatile and less dispensable to your employer and will likely generate unexpected opportunities down the road.
Where do you add these magical skills, especially if your employer isn't offering training in them? The Internet, of course. Education and skills training has experienced its own share of change lately, and there's plenty of upside for the knowledge-thirsty IT pro: Loads of readily available, online classes for developing new skills across the technical spectrum. Best of all, many of these learning opportunities come at no cost to students -- so the only thing you're really putting on the line is your time and energy. Admittedly, those are not finite resources -- but you can tackle new learning and career advancement chances with minimal risks.
This is plenty true of the still-young big data universe, whether you're looking to just get a basic primer on the big data landscape or become a serious (and in-demand) expert in Hadoop, data mining and visualization, or other areas. Keep in mind, too, that it's not merely about specific technologies or programming languages. It can be just as important to learn and hone related subject matters that help in developing deep understanding of what all that information really means, a less tangible skill set that employers and CIOs are likely to emphasize going forward.
2. Big Data And Hadoop Essentials
This basic intro to some of the key technologies, players, and problems in big data is a good way to dip your toe in the big data ocean with little risk before moving on to more advanced work. You simply can't complain about the price tag: $0.
3. Intro To Hadoop And MapReduce
Once you've got the background and basics down, it's time to get your hands dirty. This course requires you to do just that with Hadoop, including learning Hadoop Distributed File System (HDFS) and writing programs in MapReduce. The one-month course is $150, though you can do the first two weeks free to ensure it meets your needs and expectations. A working knowledge of Python (a language with plenty of its own online learning options) is recommended before beginning.
4. Massively Parallel Computing
One of the most basic problems of big data is that it will quickly crush traditional, centralized computing approaches and resources. Enter massively parallel computing to better serve the ever-growing mounds of data that people and organizations generate in the digital age. "In this course, students get hands-on experience in developing software for massively parallel computing resources," the description says. Topics and technologies covered include clusters, cloud, MapReduce, Hadoop, and Amazon's EC2 cloud.
5. Data Analysis & Statistical Inference
Statistics often pops up on lists of related skills and disciplines that can prove useful in kickstarting a big data career. This free massive open online course (MOOC) from Duke University directly connects the dots among the field of statistics and data collection, analysis, and understanding. Note: The next session starts Sept. 1.
6. Learn The R Programming Language
While we're on the subject: the R language for statistical computing (which is included in Data Analysis & Statistical Inference, on the previous slide) has become a popular choice for data visualization and, as a result, is a growing asset on a data pro's resume. Code School ($29/month for unlimited access, no long-term commitment) offers an R course in its elective path.
7. Java For Complete Beginners
Settle down, hardcore developer: This isn't the course for you. Rather, IT pros that have toiled outside of the programming realm -- or have just never worked with Java before -- but want to better position themselves for data opportunities may want to invest time in learning the language. A key reason: Hadoop is Java-based. While knowing Java isn't always a prerequisite for a big data gig, it certainly helps, especially if you want to write code. This free, on-demand course is a good place to start. Note that once you've got a handle on the programming language, at least one exec advises getting up to snuff elsewhere in the Java ecosystem (such as libraries), too.
8.Advanced Data Structures
Much of the business attention to big data is understandably focused on the bottom (or top) line: How does this help us make (or save) money? But information must be accessible in an efficient manner before any company can begin to find value in it. This free course from MIT explores the current major research (and its findings) on data structures, an area of critical importance in the information age -- and one where extensive knowledge is likely to be sought-after on big data teams.
9. Artificial Intelligence / Machine Learning
You don't need a PhD to predict that machine learning will be an increasingly popular topic in the coming years -- robot room service, anyone? -- especially as practical applications of the Internet of Things go mainstream. Expect plenty of big data implications on this front, too, not just from a learning standpoint but an analytics perspective, too. This free course from Stanford's Engineering Everywhere program covers data mining, speech recognition, text and Web data processing, and other topics.
10. Introduction to Philosophy
A philosophy course on a big data curriculum? Have we lost our minds? Not if you ask IT recruiter Jeff Remis, who told us recently that the best big data pros he works with share a strong understanding of philosophy, something that helps separate those who can mine and manage data from those who can also understand it. This introductory MOOC begins by trying to answer a very basic -- we're paraphrasing here -- question: Just what the heck isphilosophy, anyway?
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