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Difference between AI and Data Science: An Overview

Artificial Intelligence (AI) and Data Science are often used interchangeably among business leaders, but,u00a0they do share some differences. To clear your confusion between the two, this article mentions the differences.u00a0<br>

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Difference between AI and Data Science: An Overview

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  1. DifferencebetweenAIandDataScience: AnOverview ArtificialIntelligence(AI)andDataScienceareoftenusedinterchangeably amongbusiness leaders, but,they do share some differences. Toclearyour confusion betweenthetwo,thisarticlementionsthedifferences. Firstofall,letusdiscusswherewehearsuchwords.Thesewordsarefrequently usedwhenthewordslike BigData,analytics,machine learning,statistics,data mining,naturallanguageprocessing(NLP),chatbots,andotherspopinfrontof us. BothAIandDataSciencehavechangedourworldoftechnologyvery considerably. ArtificialIntelligence TheperfectdefinitionofArtificialIntelligencevariesfrompersontoperson.It highly dependsuponthe personwhom youask.Everyindividual workinginthe sectoroftechnologywillhavehisversionofthedefinition.Somemighttakethis as ahumanoid whileothersmight consider thisasatoolto explore space orfight againstvarious ailments. Thedefinition is,however, avery easyone as given by MarvinMinskyandJohnMcCarthy,whichstates, ‘it isabranchofsciencethat deals with training computersto performhuman activities.’ Therecenterahaswitnessedamoreelaborated versionofthisdefinition. According toanAI researcher atGoogle,FrancoisChollet stated thatAIis nothingbutamachine'sabilitytoadaptandimproviseinanewenvironment. It also includedtheunique abilitytoutilizethe knowledgeandapply itincertain unexpected scenarios. ThisiswhatAImeans. It isan after-the-process, the outcomeofMachineLearning.MLmakesAIhappen.Theyemphasizepatterns andlookoutforconclusions.SowecancomprehendthatAIisanelaborated form or outputofMachine Learning. AIinvolvescertainkindsofdatathat are standardizedintheformofembeddingandvectors.The useofAIisinvolvedin varyingindustriessuchashealthcare,transport,automation,manufacturing,and manymore.AIusesahighamountofscientificprocessing,unlikeDataScience that typically involvesanalyzing data andstatistics. DataScience

  2. Data Scienceisoneofthe most discussed andhottestjobs inthepresenttime. DataScienceisaperfectamalgamationofmachinelearning,scientificmethods, algorithms,structuredandunstructureddata,andappliedscientificknowledge andactions toextract hiddenmeaning.Extractingvaluesandputtingthemto workiswhatadatascientistdoes.Thisdoesinvolvemachinelearning,though,it isverydifferentfromArtificialIntelligence.WhereArtificialIntelligenceinvolves computeralgorithms,DataScienceinvolvesstatisticalanalysisandtechniques andMachineLearningisthelinkthatconnectsthetwo.MachineLearningisthe characteristicofboth,DataScienceandArtificialIntelligence.Datasciencehas becomevery importantinthecontemporary ITworld.Manycompaniescrucially hireDataScientiststo performvariousimportanttasks includingthe decision- makingprocess.DataScienceisusedinvariousindustrieswhichareinvolvedin the processing of structuredandunstructured data. DataScientists make predictionsaboutthecompanybycarefulobservance,appliedknowledge,and machinelearning methods. Conclusion Both AIandDataSciencework handinhand,but theyarenotpart ofone another.Bothtermsareseparateandhaveindividualexistence,thoughthey workinaclose-knitenvironment. AI requiresdeeperknowledgethanData Science.It'sallabouttheinsights.Boththeprofessionsareinhighdemandand payverywell.

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