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Distinguishing Data Science With Artificial Intelligence

Both Data Science & Artificial Intelligence are among the new-age revolutionary technologies in the field of computer science. With the growing prominence of Big Data, the demand for Data Science & AI technologies is exponentially increasing especially in IT, Business, Healthcare & Industrial sectors. Data Science deals with the process of extracting the information encrypted from Big Data & converts this information into actionable insights whereas Artificial Intelligence deals with the process presenting machines & computer systems with self learning & self evolving capabilities just like the characteristics of our human intelligence.

Artificial Intelligence can also be interpreted as a very advanced concept of Data Science. N some specific cases, Data Science makes use of advanced algorithms in AI explore deep inside Big Data. Currently, there is a lot of demand for the skilled & certified Data Science experts who are also having knowledge of Artificial Intelligence.

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Distinguishing Data Science with Artificial intelligence:

  • Scope

As the technology of Artificial Intelligence is still in its early stages of development process, it is having a very limited scope the doesn’t exceed beyond Machine Learning algorithms, whereas being a multidisciplinary field, Data Science has a very large scope spread across different areas.

  • Type of Data

As of now, Artificial Intelligence is only capable of processing standardized data, whereas being interdisciplinary inn nature, Data Science makes use of numerous techniques & technologies to deal with Big Data of any type, size, & format.

  • Tools

Artificial Intelligence relies heavily on the use of tools like TensorFlow, PyTorch, Kaffe, Scikit-learn, whereas Data Science uses tools like Keras, SPSS, SAS, Python, R, etc.

  • Applications:

Artificial Intelligence is extensively used in areas like Healthcare, IT, Automobile, Robotics, Business, Defence, Pharmaceutical sectors, whereas Data Science is being used in IT, Business, Banking, Marketing, Telecommunication & several other sectors.

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