Study programme 2022-2023 | Français | ||
Data Analytics for Smart Grids | |||
Learning Activity |
Code | Lecturer(s) | Associate Lecturer(s) | Subsitute Lecturer(s) et other(s) | Establishment |
---|---|---|---|---|
I-GELE-104 |
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Language of instruction | Language of assessment | HT(*) | HTPE(*) | HTPS(*) | HR(*) | HD(*) | Term |
---|---|---|---|---|---|---|---|
Anglais | Anglais, Français | 12 | 4 | 0 | 0 | 0 | Q1 |
Content of Learning Activity
Course (12h): needs in terms of data anlytics in modern electric power systems, supervised learning (regularised polynomial regression, classification - logistic regression, cross-validation, bias-variance trade-off, introduction to advanced models), unsupervised learning (clustering - K-means, principal component analysis)
Pratical work (4h): Jupyter notebooks in Python to illustrate the main algoritms seen above.
Required Learning Resources/Tools
Course slides
Recommended Learning Resources/Tools
Not applicable
Other Recommended Reading
Not applicable
Mode of delivery
Type of Teaching Activity/Activities
Evaluations
The assessment methods of the Learning Activity (AA) are specified in the course description of the corresponding Educational Component (UE)