Data Science - Revision history

User at 19:55, 5 September 2023

2023-09-05T19:55:06Z

User at 12:14, 12 January 2023

2023-01-12T12:14:17Z

User at 07:09, 16 October 2022

2022-10-16T07:09:21Z

User at 23:29, 15 October 2022

2022-10-15T23:29:58Z

User: Created page with "'''Content Coming Soon'''"

2018-12-20T00:44:52Z

Created page with "'''Content Coming Soon'''"

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'''Content Coming Soon'''

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 == What is Data Science? ==
+'''Data Science''' is an interdisciplinary field that involves using scientific methods, processes, algorithms, and systems to extract knowledge and insights from data in various forms, both structured and unstructured. It encompasses a wide range of techniques and technologies, including machine learning, statistical modeling, data mining, and visualization.
 The main steps of a data science project include:
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 *Communication and reporting: This step involves communicating the insights and findings to stakeholders and creating reports and visualizations to present the results.
-Data Science is a multidisciplinary field that requires a combination of skills including statistical modeling, programming, domain knowledge, data visualization and communication skills. Data Scientists use a combination of these skills to extract insights from data and to develop models that can be used to make predictions or decisions.
+Data Science is a multidisciplinary field that requires a combination of skills including statistical modeling, programming, domain knowledge, data visualization, and communication skills. Data Scientists use a combination of these skills to extract insights from data and to develop models that can be used to make predictions or decisions.
 == See Also ==
+*[[Machine Learning]] - A subfield of data science focused on algorithms and statistical models.
+*[[Data Analytics]] - Closely related to data science, involves analyzing raw data to make conclusions.
+*[[Big Data]] - Data science often deals with large, complex data sets.
+*[[Data Mining]] - Techniques for discovering patterns in large data sets, a component of data science.
+*[[Artificial Intelligence (AI)]] - Data science often feeds into AI applications.
-== References ==
+*[[Data Visualization]] - Representing data graphically, an important aspect of data science.
-<references />
+*[[Natural Language Processing (NLP)]] - A specialized area within data science.

← Older revision		Revision as of 12:14, 12 January 2023
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−	'''~~Content Coming Soon~~'''	+	== What is Data Science? ==
		+
		+	'''Data science''' is an interdisciplinary field that involves using scientific methods, processes, algorithms, and systems to extract knowledge and insights from data in various forms, both structured and unstructured. It encompasses a wide range of techniques and technologies, including machine learning, statistical modeling, data mining, and visualization.
		+
		+	The main steps of a data science project include:
		+	*Problem definition and understanding the data: This step involves defining the problem to be solved, understanding the data that is available, and identifying what insights are needed.
		+	*Data acquisition and preparation: This step involves collecting and preparing the data for analysis. This can include tasks such as data cleaning, data integration, and data transformation.
		+	*Data exploration and analysis: This step involves exploring the data, identifying patterns and trends, and building models to make predictions or gain insights.
		+	*Model evaluation and deployment: This step involves evaluating the performance of the models, and deploying the best-performing models to production.
		+	*Communication and reporting: This step involves communicating the insights and findings to stakeholders and creating reports and visualizations to present the results.
		+
		+	Data Science is a multidisciplinary field that requires a combination of skills including statistical modeling, programming, domain knowledge, data visualization and communication skills. Data Scientists use a combination of these skills to extract insights from data and to develop models that can be used to make predictions or decisions.

← Older revision		Revision as of 07:09, 16 October 2022
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	== See Also ==		== See Also ==
−	*[[Data]]	+
−	*[[Business_Strategy\|Business Strategy]]
−	*[[IT_Strategy_(Information_Technology_Strategy)\|IT Strategy]]
−	*[[E-Strategy\|e-Strategy]]
−	*[[IT_Governance\|IT Governance]]
−	*[[Enterprise_Architecture\|Enterprise Architecture]]
−	*[[IT_Sourcing_(Information_Technology_Sourcing)\|IT Sourcing]]
−	*[[IT Operations_(Information_Technology_Operations)\|IT Operations]]
−	*[[Chief_Information_Officer_(CIO)\|CIO]]

← Older revision		Revision as of 23:29, 15 October 2022
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	'''Content Coming Soon'''		'''Content Coming Soon'''
		+
		+
		+
		+	== See Also ==
		+	*[[Data]]
		+	*[[Business_Strategy\|Business Strategy]]
		+	*[[IT_Strategy_(Information_Technology_Strategy)\|IT Strategy]]
		+	*[[E-Strategy\|e-Strategy]]
		+	*[[IT_Governance\|IT Governance]]
		+	*[[Enterprise_Architecture\|Enterprise Architecture]]
		+	*[[IT_Sourcing_(Information_Technology_Sourcing)\|IT Sourcing]]
		+	*[[IT Operations_(Information_Technology_Operations)\|IT Operations]]
		+	*[[Chief_Information_Officer_(CIO)\|CIO]]
		+
		+
		+
		+
		+	== References ==
		+	<references />