Artificial Intelligence Engineering
GPTKB entity
Statements (50)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
gptkb:academic
|
| gptkbp:appliesTo |
gptkb:machine_learning
data science systems engineering software engineering principles |
| gptkbp:employs |
gptkb:architecture
cloud computing user experience design project management risk management version control data engineering continuous integration collaborative development agile methodologies model interpretability requirements engineering ethical guidelines model monitoring model validation performance optimization continuous deployment testing automation security best practices model governance model retraining cross-functional teams compliance standards DevOps practices MLOps practices privacy best practices |
| gptkbp:focusesOn |
deployment of AI systems
design of AI systems development of AI systems maintenance of AI systems |
| gptkbp:goal |
build ethical AI systems
build maintainable AI systems build reliable AI systems build scalable AI systems |
| https://www.w3.org/2000/01/rdf-schema#label |
Artificial Intelligence Engineering
|
| gptkbp:includes |
AI model lifecycle management
AI system deployment AI system integration AI system monitoring AI system testing |
| gptkbp:relatedTo |
gptkb:artificial_intelligence
engineering |
| gptkbp:taughtAt |
universities
|
| gptkbp:bfsParent |
gptkb:Escuela_Superior_de_Cómputo
|
| gptkbp:bfsLayer |
7
|