Data science, machine learning, artificial intelligence, automation, data analysis, data mining, data compression, data extraction, data extrapolation: these are the phrases you are simultaneously familiar with but not sure where it comes into your everyday work. Isn’t data analysis just on Excel? Can’t we just find all this information by using SQL? Or the ever-centering question: should I switch to data science?Read More
A common question asked by those who care the most about their education & deciding if their time should be best spent in graduate school or if they need to move onto bigger or better ways of getting their education for data science jobs: do I need a master’s to become a data scientist? It is a very heated question & theDevMasters would like to contribute to clearing up with what we work best with: data.Read More
The number one question asked by people who attend our webinars & in-person events that has now been asked too many times to not be turned into a blog post: what are the four skills necessary to become a data scientist?
In any order of importance, they are: programming, statistics, communication, & domain expertise.Read More
Machine learning is a subfield of computer science that evolved from the study of pattern recognition and computational theory in artificial intelligence and data science. In 1959, Arthur Samuel defined it as a "Field of study that gives computers the ability to learn without being explicitly programmed".Read More