DATA SCIENCE

Data Science Overview

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Created by raj kumar
Last updated Tue, 14-May-2024
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Course overview

Data science is an interdisciplinary field that involves extracting insights and knowledge from structured and unstructured data. It combines techniques from statistics, mathematics, computer science, and domain expertise to analyze complex datasets and make data-driven decisions.

The data science process typically begins with data collection, where raw data is gathered from various sources such as databases, sensors, social media, and the internet. This data is then cleaned, processed, and transformed into a usable format for analysis.

Exploratory data analysis (EDA) is performed to understand the underlying patterns, trends, and relationships within the data. This involves using statistical methods, data visualization techniques, and machine learning algorithms to uncover insights and identify potential correlations.

Machine learning plays a crucial role in data science, allowing algorithms to learn from data and make predictions or decisions without explicit programming. Supervised learning, unsupervised learning, and reinforcement learning are common types of machine learning techniques used in data science projects.

Data science has numerous applications across various industries

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Updated Thu, 28-Mar-2024
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raj kumar

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