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Resonance -relating to sound, movement, space and time - — DAN4378.01

Instructor: Martin Landz
Days & Time: WE 4:10pm-6:00pm
Credits: 2

A class, a laboratory that explores the relationship between movement and sound, starting with the phenomenology of sound and acoustics, and considering the translation from sound to movement.

Incorporates listening techniques and sensory perception and encourages participants, through improvisation, to draw from movement, sound, space and memory interchangeably. They will be guided through exercises that help make decisions based on assessment, observation, listening and decision making.

Orchestration — MCO4133.01

Instructor: Nicholas Brooke
Days & Time: WE 4:10pm-6:00pm
Credits: 2

A primer in orchestration, for students who are selected to write for Sage City Symphony. We will pore over the 19th and 20th century orchestral repertoire, getting to know instruments, ranges, and agilities. Analysis, piano reduction, and orchestration from grand staff will be used to internalize and hear orchestration. Students will be expected to create and get feedback on textural sketches of their future pieces.

Post-Mao Chinese Rock and Roll — CHI4511.01

Instructor: Ginger Lin
Days & Time: TU,FR 2:10pm-4:00pm
Credits: 4

This course examines the evolution of Chinese rock music in the post-Mao era, focusing on influential artists such as Cui Jian, Dou Wei, and Zuo Xiao Zu Zhou. Their lyrics not only reflect significant historical and social transformations in China after Mao but also capture the cultural shifts brought by economic reforms, the one-child policy, and the experiences of migrant workers in major cities.

Data Structures and Algorithms — CS4388.01

Instructor: Darcy Otto
Days & Time: TU,FR 2:10pm-4:00pm
Credits: 4

How do we organize data to solve complex problems efficiently? This course studies the fundamental structures and algorithms that form the cornerstone of computational problem-solving. Building upon the programming foundations established in CS1, we will explore how algorithmic thinking and sophisticated data organization enables us to tackle increasingly challenging computational problems.