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Artificial intelligence has been around since the 1950s. First proposed as a concept by Alan Turing early in the decade, it was solidified as a field of study at the 1956 Dartmouth Conference, which used AI as a heading to encompass language simulation, neural networks modeled on human brains and expert systems. Though merely a concept then, AI was made possible by machine learning which used algorithms to examine data in order to make a decision or prediction.

As the AI wave becomes transformational across end-markets from enterprise to consumer platforms, from cybersecurity to robotics, the demand for data scientists is growing exponentially. The role of data scientists in this technology will assume a new level of importance and will evolve in a similar fashion to what we saw happen in the field of computer sciences with the development of computing.

Much like developers started using software for a broad array of applications, they started developing tools (e.g. programming languages, libraries, etc.) that would allow them to program at a higher level and tackle increasingly more complex problems.

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