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
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)
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.