Lecture: Understanding data

Lecture: Understanding data

Administrative information

Title Understanding Data
Duration 60
Module A
Lesson Type Lecture
Focus Technical - Foundations of AI
Topic Understanding Data

 

Keywords

data types,data transformation,data visualisation,

 

Learning Goals

  • Learner acquires demonstrable knowledge of data forms used in AI.
  • Learner can talk about data using the right terminology (e.g., features, variables, observations).
  • Learner knows the different data types and knows how to transform them (e.g., nominal, ordinal).
  • Learner knows the most common measures for data description (e.g., mean, median, standard deviation) and knows how to calculate them.
  • Learner acquires demonstrable knowledge of how data are described via measures and visualisation.
  • Learner knows the most common graphs and knows how to pick a visualisation, matching the given data.

 

Expected Preparation

Learning Events to be Completed Before

None.

Obligatory for Students

None.

Optional for Students

None.

References and background for students:

None.

Recommended for Teachers

None.

Lesson Materials

 

The materials of this learning event are available under CC BY-NC-SA 4.0.

 

Instructions for Teachers

In this lecture we introduce the students to data (and determine the correct terminology). This lecture has no prerequisites. It can be followed by the tutorial on data understanding. See the lesson plan: Tutorial: Understanding Data

Topics to cover

  • Introduction to what data are, how they can be useful and in what form they are used in AI (15mins)
  • Introduction to data types and transformations (15mins)
  • Measures for data description (15mins)
  • Data visualisation (15mins)

 

More information

Click here for an overview of all lesson plans of the master human centred AI

Please visit the home page of the consortium HCAIM

Acknowledgements

The Human-Centered AI Masters programme was co-financed by the Connecting Europe Facility of the European Union Under Grant №CEF-TC-2020-1 Digital Skills 2020-EU-IA-0068.

The materials of this learning event are available under CC BY-NC-SA 4.0

 

The HCAIM consortium consists of three excellence centres, three SMEs and four Universities

HCAIM Consortium

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    Auteur
    HCAIM Consortium
    Laatst gewijzigd
    2024-05-15 11:05:14
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    HCAIM Consortium. (z.d.).

    Acknowledgement

    https://maken.wikiwijs.nl/198386/Acknowledgement

    HCAIM Consortium. (z.d.).

    Lecture: Duty Ethics

    https://maken.wikiwijs.nl/198966/Lecture__Duty_Ethics

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