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The fields have evolved such that to work as a dataanalyst who views, manages and accesses data, you need to know Structured Query Language (SQL) as well as math, statistics, data visualization (to present the results to stakeholders) and data mining.
Key Components In Data Science, key components include data cleaning, Exploratory Data Analysis, and model building using statistical techniques. ML focuses on algorithms like decision trees, neural networks, and supportvectormachines for pattern recognition. billion in 2023 to an impressive $225.91
Applications of Data Science Data Science is not confined to one sector; its applications span multiple industries, transforming organisations’ operations. From healthcare to marketing, Data Science drives innovation by providing critical insights.
(Or even better than that) Machine learning has transformed the way businesses operate by automating processes, analyzing data patterns, and improving decision-making. It plays a crucial role in areas like customer segmentation, fraud detection, and predictiveanalytics.
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