Data Science has emerged as a hot dip topic over the last few years but long before that in 2012, it was declared as “The Sexiest Job of the 21st Century” in an article in Harvard Business Review. If you wonder what had made this domain so hotly discussed today, one reason could be the existence of huge data sets to work upon.
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.
Regardless of industries or companies, adoption of technology has a multitude of positive impacts on business growth as it paves the path to gain profit. It impacts every aspect of a business – from operations and effectiveness to future growth. Today, data is being collected by businesses as well as organizations through every possible way. From digital clicks and mobile app usage to interactions on social media – everything leaves a data fingerprint that’s completely unique to its creator.
As more and more companies are trying to become data-driven, it looks like each of them will need to employ data science, making the demand for data scientists even greater. The world is becoming connected increasingly and a huge amount of data is being generated every single day and businesses are trying their best to make use of this data to rise above the competition.