The hottest new courses at universities around the world are in the field. Data Science seems to have well earned its title as the "sexiest job of the 21st century." But with all this commotion about the field, many wonder whether the trend toward Careers in Data Science is all just a fad. Why hedge your education, career and future on a bet? It's reasonable to have these hesitations.
Artificial intelligence jobs are not a new phenomenon, but the AI job market is growing as AI market itself is seeing rapid expansion. According to research firm IDC, AI is currently seeing an annual growth rate approach 40 percent. Amid these changes, AI job titles have changed and expanded – and AI paychecks are heading skyward. Earlier roles were "statistician" or "mathematician," while today you'll hear newer terms like "data scientist" and "predictive analytics expert." The rapid emergence of new AI titles reflects the fact that AI has become practical for mainstream use as the result of affordable cloud computing and storage costs, a change from prohibitively expensive supercomputers.
It is the heyday for Data Science... Data Science seems to have well earned its title as the "sexiest job of the 21st century." But with all this commotion about the field, many wonder whether the trend toward Careers in Data Science is all just a fad. Why hedge your education, career and future on a bet? It's reasonable to have these hesitations. All Data Scientists worth their salt should know the importance of working with facts rather than hunches.
What is a data scientist? If you ask the Harvard Business Review, it's the "sexiest job of the 21st century." If you ask a technologist interested in crunching data, they'll tell you it's a potentially lucrative, intellectually fulfilling career. And if you ask a CEO, they'll probably say that data scientists mean the difference between strategic success and failure. But how do you actually become one? At the most basic level, data scientists analyze massive datasets for insights that can change how companies operate and strategize. As terms, "data scientist" and "data science" are relatively new, first appearing a little over a decade ago (roughly around the time that "Big Data" emerged into the mainstream as a buzzword, which isn't a coincidence).
Summary: In which we attempt to answer the question, how does someone in school or recently out enter the exciting world of data science. There is no question that comes up more frequently than'how do I become a data scientist'. I've actually written several articles on this topic (and will reference them liberally in this post) but they lacked the global perspective that potential new entrants to data science want. I'm going to try to resolve here. I thought about changing the title to "Doing Data Science" instead of becoming a Data Scientist to focus on the activity and not just the job title. There are two good reasons.