Difference Between Data Science and Artificial Intelligence
Data Science: In 1974, Peter Naur proposed data science as an alternative name for computer science. Data Science is a subset of Artificial Intelligence. Simply data science is a collection of data to analyze and we make a decision on behalf of it. It uses scientific methods, processes, algorithms, and insights from many structural and unstructured data. the person who works on data science is known as data scientists.
Artificial Intelligence: At a conference at Dartmouth College, Hanover, New Hampshire, where the term Artificial intelligence was coined (1956). It’s a human-like intelligence provided to the machines where machines act think as humanly. They solve problems faster than human beings. Speech recognition, translation tools, etc are the building areas of AI. AI is all about the machine learning deep learning etc. We can emulate cognition and human understanding to a certain level.
| Data science | Artificial Intelligence |
|---|---|
| Data Science is a detailed process that mainly involves pre- processing analysis, visualization and prediction. | AI(short) is the implementation of a predective model to forecast future events and trends. |
| It has a high degree of scientific processing. | It has a lot of high level of complex processing. |
| By using the concept of data science, we can build complex models about statistics and facts about data. | By using this we emulate cognition human understanding to a certain level. |
| It uses the technique of data analysis and data analytics. | It uses a lot of machine learning techniques. |
| Its knowledge was established to find hidden patterns and trends in the data. | Its knowledge is all about imparting some autonomy to a data model. |
| R, Python, etc are the tools used in data science. | Tensorflow, scikit-learn, Kaffee, etc are the tools used in AI. |
| Its applications are advertising, marketing, Healthcare, etc. | Its application are robotics, automation, etc. |
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