Course program
The course has a theoretical-practical orientation: theoretical exchange and critical discussions will be combined with practical sessions (lab-based sessions) through which participants will work collaboratively. The results will be publicly presented on the last day of the course.
Hours: 50
August 30th – September, 4th, 2021
The course is organized around FIVE TRACKS
Course Schedule
Track A: Digital Display Spaces
Track A, Greg Niemeyer (UC Berkeley) Niemeyer will work with participants in configuring digital spaces for exhibitions on virtual platforms such as newart.city and modzilla hub. Techniques include basic modelling and animation, .fbx or .glb file format, spatial strategies for virtual engagement, data visualization and local sound synchronization in virtual spaces. Track A participants will create content and curate content produced in the other Tracks to cumulate in an online virtual exhibit about DAHSS 2021.
Track B: Data Science
Track C 3D Data, Modeling, and Rendering
Track D: AI + Computer Vision
Track E: Natural Language Processing (NLP)
Track E, led by Yadira Lizama Mué (CulturePlex Lab, Western Ontario University) will explore the power of NLP to study what textual data can tell us about art on a large scale. NLP is a field of Artificial Intelligence that centers around measuring human language to make it intelligible to machines. It combines the power of linguistics and computer science to contemplate the guidelines and structure of language and make intelligent systems fit for comprehension, breaking down, and separating significance from text and speech. We’ll learn a wide range of NLP topics, such as regular expressions, word tokenization, named-entity recognition, topics extraction, sentiment analysis, and text classification. We’ll also gain practical experience in the use of tools such as Spacy, alongside libraries that utilize deep learning to solve common NLP problems. We will have the opportunity to explore collections of texts related to art included in H.W.Wilson’s Art Full Text database, Project Muse, Wikipedia, and hundreds of media articles related to art exhibitions.