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Level: Undergraduate, Graduate
Division: Parsons The New School for Design
School: School of Art, Media and Technology
Department: Art, Media & Technology
Course Number: PSAM 5600
Course Format: Studio
Location: NYC campus
Permission Required: No
These courses are special topical electives, often taught in new or experimental subjects, and rotate frequently. The following will be offered in spring 2016: MATTERHACKERS: RADICAL METHODS OF MATERIAL MAKING: This course will take students on a journey to the furthest edges of our new material spectrum and challenge them think about how they might hack this new material future. Students will gain an overview of new fabrication methods (Synthetic biology, genetic engineering, 4D printing), a palette of new materials (biomaterials, nanomaterials, programmable, DNA), and will investigate how these concepts could be applied to real world situations. We will cover branding, design, IP, ethics and how current industries and startups are developing radical products and processes. INTERACTIVE SPACES: This class will function as a primer and a workshop around creating site-specific, architectural, technology-based interventions. We will cover conceptual approaches, pragmatic concerns, and precedents in art and architecture. Our major focus will be around developing and prototyping concepts, which will include a range of technical and non-technical methodologies. GAME AESTHETICS: In this studio we take a step away from the usual game design frameworks and focus on the underlying formal structures of games. We will study the range of existing game frameworks, using both accessible libraries like Paolo Pedercini’s P5Play in P5.js and sophisticated modern languages like Haxe and Luxe to develop experimental and expressive games, build our own frameworks, and develop a greatly extendable set of advanced programming skills. Students will investigate the ties between game design and procedurality and the relationship of the structure of representation to the creative forms that can emerge, using game and game framework programming as a means of discovery and self-expression. MACHINE LEARNING: Machine learning is the systematic study of algorithms and systems that improve their knowledge and performance with experience. Collecting and analyzing data through machine learning algorithms and models can uncover complex patterns in massive amounts to data to make more accurate predictions and to reveal coherent dimensions. The course covers classification, regression, clustering, subgroup, and association models to predict and describe, using supervised and unsupervised learning methods. Special attention will be given to models and techniques that aid and support the visualization of complex data. An introductory course in probability and statistics (NURP 5013 or similar) and intermediate experience with a modern programming language such as JavaScript, Python, or R is necessary to take this class. Open to: All School of Art, Media & Technology graduate and upper-level undergraduate degree students
Course Open to: Degree Students with Restrictions