Data science is a field that’s hotly discussed today among various spheres. If you’re wondering what drives this growing interest in the field, this simple piece of news can offer some insight. According to IBM, a whopping 2.7 million data scientist jobs will need to be filled by the year 2020, and the figure is just for the US. If you consider how businesses and organizations around the world are trying to derive meaningful and actionable insights from data they have collected over the years and building data science teams for the process, you can imagine how lucrative this field is likely to become in the near future. If you take a look at IBM’s predictive statistics, you’ll also understand how valuable a background in data science could become over the forthcoming years.
The job of data scientist is being considered as one of the hottest professions today. This has mainly happened because of the highly attractive data scientist salary that’s being offered by the organizations. As a result, a significant number of people from almost every walk of the tech landscape are thinking of a career change and planning to step into the data science landscape.
Data science has become the buzzword over the last few years. Companies and organizations in virtually every industry are looking to get the optimum value from their rapidly increasing information resources. As we are living today in a data-driven age where interconnected humans and devices are churning out a huge volume of data every second relentlessly, it has become necessary for organizations and companies to take optimum advantage of their internal data assets and scrutinize the integration of hundreds of third-party data sources.
Machine learning refers to a data analytics technique, which teaches computers to perform what naturally comes to humans – learning from experience. The term was coined in 1959 by Arthur Samuel – an American pioneer in the fields of artificial intelligence and gaming. Machine learning is unquestionably the latest buzzword in the tech landscape as it’s one of the most interesting and promising subfields of computer science.
The century’s hottest job is all about acquiring and mastering the right skills aligned to it. If you’re planning to learn data science to step into the field, you’ve to obtain an excellent grasp of the required skills. Assuming you already have a natural curiosity and a good understanding of the concepts of mathematics and statistics, what should you learn next to become a data scientist? You’ve to learn coding and be exceptionally good at it. This comes through vigorous practice and study of various programming languages. Exceptional knowledge of Python and R, in particular, makes the path quite easier if you plan to learn data science.
Data bootcamps aren’t cheap. When you consider how these bootcamps deliver extremely targeted and effective information for fast-paced learning coupled with lots of hands-on experience, the cost they charge may seem fit.