SKILL OF DATA SCIENC

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Data science is the
study of data to extract meaningful insights for
business,institute and organisation. It is a
multidisciplinary approach that combines
principles and practices from the fields of
mathematics, statistics, artificial intelligence,
and computer engineering to analyse large amounts
of data.
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• Programming Skills
• Proficiency in one or more programming languages
  such as Python, R, or SQL is essential for data
  science. These languages are commonly used for
  data manipulation, analysis, and modelling.

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• Statistics and Mathematics
• A solid foundation in statistics and mathematics
  is crucial for data science. Knowledge of
  statistical methods, probability theory, linear
  algebra, and calculus is necessary for performing
  data analysis and modelling.

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• Data
• Wrangling
• Data wrangling is the process of cleaning,
  transforming, and preparing raw data for
  analysis. It involves skills in data cleaning,
  data preprocessing, and data integration.

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• Machine
• Learning
• Machine learning is an important aspect of data
  science, which involves building models that can
  learn from data to make predictions and
  classifications. Knowledge of machine learning
  algorithms and their applications is essential.

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Data Visualization
Data visualisation is the process of presenting
data in a visual form to communicate insights
effectively. Skills in data visualisation tools
such as Tableau, matplotlib, or ggplot2 are
necessary for creating effective visualisations.
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Communication Skills
Data scientists need to be able to communicate
their findings and insights effectively to
non-technical stakeholders. They need to have
strong communication skills, both written and
verbal, to explain complex data science concepts
to a wider audience.
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Skill of Data Science
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