VECTOR | [3-0-0:3] |
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DESCRIPTION | As Machine Learning (ML) permeates numerous aspects of culture, industry, and scholarship, it is crucial for the next generation of computational artists to be ML-literate, possessing the ability to critically evaluate and apply this rapidly evolving technology. Through hands-on experience with cutting-edge ML tools, students will hone their skills in this domain and establish critical perspectives on the strengths and limitations of current methods. This course employs free, open-source ML toolkits, enabling students to become familiar with various classification and regression models, RNNs, Convolutional Neural Networks, Transfer Learning, large language models, Text-to-Image generators, and more, for the purpose of implementing art projects. Each week, pertinent computational artworks utilizing various techniques are introduced, analyzed, and discussed. |
Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
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L01 (6062) | 22-JAN-2024 - 18-FEB-2024 Tu 10:30AM - 01:20PM | Rm 201, W1 | PAPATHEODOROU, Theodoros | 20 | 7 | 13 | 0 | |
19-FEB-2024 - 10-MAY-2024 Tu 10:30AM - 01:20PM | Rm 105, E3 | PAPATHEODOROU, Theodoros |
ATTRIBUTES | Common Core: Broadening (Arts) |
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DESCRIPTION | This course introduces students to programming graphics and interaction for computational media and arts. Students learn the principles, algorithms, and coding frameworks for creating graphics and interaction with machines while also sharpening their sense of aesthetics. Each week, the relevant computational artworks employing these techniques are introduced, analyzed, and explored in practical assignments. |
Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
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L01 (6234) | Mo 10:30AM - 11:50AM | Rm 134, E1 | PAPATHEODOROU, Theodoros | 50 | 28 | 22 | 0 | |
T01 (6235) | Mo 12:00PM - 01:20PM | Rm 134, E1 | PAPATHEODOROU, Theodoros | 50 | 28 | 22 | 0 |