Both Data scientists and AI engineers must be proficient in a few common skills and topics, however, both are tasked with an entirely different set of responsibilities. Data scientists focus on data, work with data and work for data, while AI engineers implement concepts (algorithms) such as Artificial Neural Networks to develop AI-supported services or machines. The demand for AI engineers will keep growing as the global AI market sees exponential growth in the coming years, reaching $309.6 billion by 2026.

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@ankushsinglaAnkush Singla

Ankush Singla is a co-founder at Coding Ninjas and he specialized in Programming, Data & Development

It is quite hard for budding developers to decide whether they wish to become data scientists or if they wish to contribute to automation and building smarter machines. Both are highly desirable job roles with enormous scope for growth.

Data Science and AI are both valuable implementations of computing and technology. The two fields are highly dependent on each other for viable business or IT solutions that are sustainable in the long run.

Data Science and AI are massive fields on their own, boasting multiple branches and sub-divisions. Both Data scientists and AI engineers must be proficient in a few common skills and topics, however, both are tasked with an entirely different set of responsibilities. Data scientists focus on data, work with data and work for data, while AI engineers implement concepts (algorithms) such as Artificial Neural Networks to develop AI-supported services or machines.

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Picture by Burak Kebapci from Pexels.

Fundamental differences between Data Science and AI

The main difference between the two fields of study can be observed in the tools and techniques used by AI engineers and Data Scientists. While both the branches require mathematics, statistics, and programming, both the fields implement them differently. AI engineers are programming experts who program machines to implement automation or learning algorithms.

Meanwhile, Data Scientists use statistical and analytical tools in order to extract data, store data and gain insights from data. Let us look at the most important differences between the two.

In development, AI is generally the prime focus while Data Science simply supports or empowers IT and other developmental processes.

AI engineers are required to work with programming and Machine Learning. Data Scientists use mathematics, statistics, and analytical tools, very rarely requiring programming.

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Source: hackernoon.com