Today we are existing in a time of rapid technical, Scientific and industrial advancement. we can harness the computer processing power for ever more complex tasks, as they are increasing exponentially. Data Science, DS and Artificial Intelligence, AI are inter-related, but they are not the same though they fall in the same category. They have their own sets of concepts and applications; they are too popular and most sought-after technologies. These domains may have some common topics, they may overlap, however, both these technologies are unique in their own ways and their uses. To clear all our confusions, we will explore Data Science vs Artificial Intelligence. Here is Difference between data science and artificial intelligence .
Artificial Intelligence by associations combines large amounts of data through iterative aspect processing and algorithms to help computers acquire intelligence automatically. While, Data Science links frameworks by data analytical methods to extract sense, pattern that can be obtainable out of it, for analytical purposes.
Difference Between Data Science and Artificial Intelligence
The below table consists of some key variances between the two exclusive technologies:
| Comparison Factor | Data Science | Artificial Intelligence |
| Meaning | It aims at massive data for analytics and visualization | It aims in implementing data and the knowledge of machines |
| Skills | It uses Statistical techniques for development and design | It uses Algorithms for development and design |
| Technique | It uses Data Analytics technique | It uses Deep Learning and Machine Learning techniques |
| Observation | It looks for patterns in data to make well-informed decisions | It enacts intelligence in machines using data to make them reply as humans organize |
| Solving Issues | It utilizes control and program structures to solve particular issues | It utilizes control and program structures for planning and perception |
| Processing | It uses a systematic data processing for data manipulation | It uses sophisticated processing of scientific data for data manipulation |
| Graphic | It represents data in graphical formats | It uses an algorithm network node representation |
| Tools Involved | SAS, SPSS, Keras, R, Python, etc. | Caffe, Shogun, Mahout, Py-Torch, Tensor-Flow, Scikit-Learn, etc. |
| Applications | Dominantly used in Internet search engines, such as Yahoo, Bing, Google, Fraud Detection and Healthcare analysis are popular examples of Data Science etc. | Used in industries, including transport, healthcare, manufacturing, automation, Chatbots, and Voice assistants are popular applications of AI. etc. |
This all-inclusive assessment table, helps you to make an optimal decision on pursuing a profession in whichever Artificial Intelligence or Data Science.
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