Course unit
Last updated: 26/09/2024
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Course Director(s):
Key words:
Generative Adversarial Networks
Recurrent and residual networks
Attention
Transformers
Advanced architectures and models
Vision
NLP applications
Number of teaching hours
30
Fields of study
Computer Science, Information Systems
Teaching language
English
Intended learning outcomes
| On completion of the unit, the student will be capable of: |
Classification level |
Priority |
Learning assessment methods
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Percentage ratio of individual assessment
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Percentage ratio of group assessment
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Written exam:
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%
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Project submission:
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50
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%
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Individual oral exam:
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%
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Group presentation:
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%
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|
Individual presentation:
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50
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%
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Group practical exercise:
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%
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|
Individual practical exercise:
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%
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Group report:
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%
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|
Individual report:
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%
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|
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|
Other(s): %
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Programme and content
| Type of teaching activity |
Content, sequencing and organisation |