Low Code Data Science is the Future

It is not a research niche anymore. Random Forests and Deep Learning networks are now available in libraries and tools, waiting to be applied to business problems and real-world data. This is so true that the focus of AI has now shifted from proposing new paradigms and new algorithms to engineering existing solutions via a standardized sequence of MLOps. When something moves away from research and becomes mainstream, other segments of the data analytics society claim access to it. Can people who haven't learned how to code, like marketing analysts, physicians, nurses, CFOs, accountants, mechanical engineers, auditing professionals, and many other professional figures, successfully implement AI solutions?