Administrative information


Title Unsupervised Learning
Duration 60 mins
Module A
Lesson Type Lecture
Focus Practical - AI Modelling
Topic Data analysis

 

Keywords


Unsupervised learning,Clustering,Advanced Clustering,Ethics,

 

Learning Goals


 

Expected Preparation


Learning Events to be Completed Before

Obligatory for Students

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


You can base this class around the slides.

Outline/time schedule


 
Duration (min) Description Concepts
5 Unsupervised learning Intro to unsupervised learning (vs supervised)
20 Clustering KMeans, K-Medoid, optimal K
20 Advanced Clustering Hierarchical clustering, DBSCAN
5 Advanced Dimensionality reduction advanced dimensionality reduction: t-SNE
5 Ethics Connection to Ethics Case study

Connection to Ethics Case study


Clustering people may enable predictions that violate privacy or draw unjust inferece, like in the following cases

 

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