Summary: Explaining data science to a non-data scientist isn’t as easy as it sounds. You may know a lot about math, tools, techniques, data, and computer architectu...
The messiest job of the 21st century The interview process is likely the most daunting task a data scientist will face in their career. The pressure and competition to ...
The value of data science multiplies when it is used and applied across the organization. Successful data science should impact the business — and that requires data sc...
Naming conventions are often quite different in statistics and data science, which causes quite a bit of confusion. Part of the problem with naming conventions is that ...
Everyone wants to restart the economy safely. Everyone. The question isn’t “if”, it’s “when” and “how” and somehow that’s when politics gets involve...
Introduction to 5-part practical guide on becoming a data scientist. Are you someone who: Has studied concepts of statistics, econometrics or mathematics? Loves reasoning...
Data science, by definition, is an interdisciplinary field which makes use of scientific processes, methods, systems, and algorithms for extracting insights and knowledge...
We will talk about two chief technologies that deal with data namely Business Analytics and Data Science. The latter is specific to customer choice, geographical influenc...
Most of the big organizations are struggling with AI transformation. Data science projects are either taking too long to complete or would never get into production. Am...
2020 is the year that AI has moved from a science experiment to business as usual. And with the arrival of AI comes the need for AI governance. How do you know that your ...