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skil of data science

https://datascienceinstitutework.blogspot.com/2023/02/skills-of-data-science.html

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skil of data science

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  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. Data Visualization: Data visualisationis 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.

  7. 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.

  8. Skill of Data Science

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