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.
Ever since the role of data scientist was considered as the century’s hottest job by the Harvard Business Review, the field has been attracting almost countless people coming from many different backgrounds. In today’s tech-driven world, almost every company or business is trying to leverage big data – from market leaders to government institutions to non-profit organizations. As a result, the demand for data scientists has become an all-time high.
Probably you’re already aware that the role of data scientists is considered as the 21st century’s sexiest job and this statement depends on the expertise, job responsibilities and salaries of data scientists. In 2018, the median base salary range was from $95,000 to $165,000 for individual contributors while for managers it was from $145,000 to $250,000.
You’ve probably seen the headlines that state the role of data scientist to be the 21st century’s sexiest job and are somewhat aware of the excellent pay packet coupled with other perks and excellent future prospect that a data scientist can enjoy. In today’s data-driven economy, businesses across the globe are constantly searching for good data scientists who can turn the huge amount of data into valuable insights. So, no wonder why people from a diverse range of fields are gearing toward a career in the field of data science. Unfortunately, a majority of the universities don’t offer major programs or degrees that are designed explicitly for data scientist training.
In today’s world, as the volume of data generated from different sources is increasing exponentially and almost in every minute, there’s an urgent need for businesses across the globe to derive actionable insights from it in order to rise above the competition. As a result, companies across the globe are desperately looking for data scientists who can handle and analyze huge datasets by using cutting edge tools and technologies to help them accomplish their business goals.