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 \documentclass{article}

\begin{document}

\title{\textbf{Data Science}}

\author{\textit{name}}

\date{June 2025}

\maketitle

\section{\Huge{What is Data Science}}

\normalsize {Data Science is an interdisciplinary field that uses a combination of statistics, computer science, and domain knowledge to extract valuable insights from data. It involves collecting, cleaning, analyzing, and visualizing large volumes of data to support decision-making and predictive modeling. With the rapid growth of digital data, data science has become essential in industries such as healthcare, finance, marketing, and technology.}

\subsection{Components of Data Science}

{The main components of data science include data collection, data processing, data analysis, and data visualization. It also involves the use of machine learning and artificial intelligence for predictive analytics. Data scientists use tools like Python, R, SQL, and software such as Tableau or Power BI to manage and analyze data. These components work together to transform raw data into actionable insights.}

\subsubsection{\textbf{Classification of Data Science:}}

Data Science can be classified into several areas such as descriptive analytics, diagnostic analytics, predictive analytics, and prescriptive analytics. Descriptive analytics focuses on what has happened, while diagnostic analytics explores the reasons behind those outcomes. 

\small{Example:recommending marketing strategies or inventory restocking plans to increase future sales. These classifications help organizations make better, data-driven decisions and improve business efficiency.}

\footnotesize{Example: analyzing patient data to determine why there was a spike in respiratory illnesses during a specific season}

\subsubsection{\textbf{Applications of Data Science:}}

\large{Data science is widely used across various domains. In healthcare, it is used for disease prediction and patient monitoring. In finance, it helps detect fraud and manage risk. E-commerce platforms use data science for recommendation systems and customer behavior analysis. It also powers technologies like self-driving cars, voice assistants, and smart city planning. The growing reliance on data makes data science a vital tool for innovation and growth.}


\end{document}


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