CBSE Class 9 AI (Artificial Intelligence) | 3. Basics of data literacy by Abraham | Learn Smarter
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3. Basics of data literacy

The chapter provides an introduction to the fundamentals of data literacy, covering the definition of data, its various types, sources, collection methods, and storage solutions. It highlights the importance of data in decision-making, analysis, and ethical considerations surrounding data privacy. Understanding how to effectively represent, analyze, and interpret data lays the groundwork for future studies in artificial intelligence and data science.

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Sections

  • 3

    Basics Of Data Literacy

    This section introduces data literacy, explaining what data is, its types, sources, collection methods, storage, and the importance of understanding and interpreting data.

    Learning Practice

  • 3.1

    What Is Data?

    Data encompasses facts, figures, or information collected for reference or analysis.

    Learning Practice

  • 3.2

    Types Of Data

    This section categorizes data into structured, unstructured, and semi-structured types, providing essential examples for each.

    Learning Practice

  • 3.2.1

    Structured Data

    Structured data refers to highly organized information that is easily searchable in databases and spreadsheets.

    Learning Practice

  • 3.2.2

    Unstructured Data

    Unstructured data refers to any data that does not have a predefined data model, making it difficult to analyze.

    Learning Practice

  • 3.2.3

    Semi-Structured Data

    Semi-structured data is a type of data that has some organizational properties but lacks the rigid structure of traditional structured data.

    Learning Practice

  • 3.3

    Sources Of Data

    Data can be sourced from various origins, including people, sensors, machines, and social media.

    Learning Practice

  • 3.4

    Importance Of Data

    Data is crucial for informed decision-making and understanding trends across various domains.

    Learning Practice

  • 3.5

    Data Collection Methods

    Data can be collected using various methods, each suitable for different types of information and contexts.

    Learning Practice

  • 3.6

    Data Storage

    This section discusses the importance of data storage, outlining various methods such as local storage, cloud storage, and databases.

    Learning Practice

  • 3.7

    Understanding Data Representation

    Understanding how to represent data effectively is crucial for analysis and communication.

    Learning Practice

  • 3.8

    Data Analysis And Interpretation

    Data analysis and interpretation involve drawing meaningful conclusions from represented data.

    Learning Practice

  • 3.9

    Data Privacy And Ethics

    This section explores the significance of data privacy and ethics in handling personal data, highlighting the importance of responsible data management.

    Learning Practice

  • 3.10

    Characteristics Of Good Data

    Good quality data is essential for accurate analysis and decision-making, characterized by accuracy, completeness, consistency, timeliness, and relevance.

    Learning Practice

References

u2ch3.pdf

Class Notes

Memorization

What we have learnt

  • Data is defined as facts or...
  • There are various types of ...
  • Data plays a crucial role i...

Final Test

Revision Tests