Introduction to Computational Thinking a

INTRO COMP THINK AND DATA SCI

This course and its co-requisite lab course will introduce students to the methods and tools used in data science to obtain insights from data. Students will learn how to analyze data arising from real-world phenomena while mastering critical concepts and skills in computer programming and statistical inference. The course will involve hands-on analysis of real-world datasets, including economic data, document collections, geographical data, and social networks. The course is ideal for students looking to increase their digital literacy and expand their use and understanding of computation and data analysis across disciplines. No prior programming or college-level math background is required.

• MW 2:40 p.m.-3:55 p.m.
• TR 6:10 p.m.-7:25 p.m.
• Instructor: Lisa Soros
  Info
• Instructor: Antonio K Moretti
  h-index: 7 Info
• 3 points

Introduction to Computational Thinking a

LAB INTRO COMP THINK DATA

This is the co-requisite lab to COMS BC 1016 (Introduction to Computational Thinking and Data Science)

This course will introduce students to the methods and tools used in data science to obtain insights from data. Students will learn how to analyze data arising from real-world phenomena while mastering critical concepts and skills in computer programming and statistical inference. The course will involve hands-on analysis of real-world datasets, including economic data, document collections, geographical data, and social networks. This class is ideal for students looking to increase their digital literacy and expand their use and understanding of computation and data analysis across disciplines. No prior programming or math background is required.

• W 11 a.m.-12:50 p.m.
• W 4:10 p.m.-6 p.m.
• F 10 a.m.-11:45 a.m.
• F 2:10 p.m.-4 p.m.
• 1 points

INDEPENDENT STUDY

Independent Study. Instructor permission required.

• Instructor: Mark Santolucito
  CULPA: 1 h-index: 8 Info
• Instructor: Antonio K Moretti
  h-index: 7 Info
• Instructor: Rebecca N Wright
  Wikipedia h-index: 34 Info
• Instructor: Brian K Plancher
  Info
• Instructor: Lisa Soros
  Info
• Instructor: Paul S Blaer
  CULPA: 46 h-index: 8 Info
• 1-4 points

PRIVACY IN A NETWORKED WORLD

The ubiquity of computers and networks in business, government, recreation, and almost all aspects of daily life has led to a proliferation of online sensitive data: data that, if used improperly, can harm the data subjects. As a result, concern about the use, ownership, control, privacy, and accuracy of these data has become a top priority. This seminar course focuses on both the technical challenges of handling sensitive data, the privacy implications of various technologies, and the policy and legal issues facing data subjects, data owners, and data users.

• W 4:10 p.m.-6 p.m.
• Instructor: Rebecca N Wright
  Wikipedia h-index: 34 Info
• 4 points

Computational Sound

COMPUTATIONAL SOUND

In this course, we explore the variety of roles that computation can play in the analysis, creation, and performance of music. We start with the fundamentals of sound in the digital domain, covering issues of representation and audio synthesis. We then move through various synthesis techniques including the additive, subtractive, frequency modulation (FM), and amplitude modulation (AM) synthesis. After covering some core DSP techniques, we put these concepts into performative practice by exploring “live coding”. In the space of live coding, we examine various programming language designs to understand how various domain specific languages (DSLs) support live coding. For the third module, we turn our focus to automated composition and analysis, addressing challenges in music information retrieval, generative art, and autonomous improvisation systems. All the while, we continue to develop our fluency in live coding by putting new topics to practice.

• TR 6:10 p.m.-7:25 p.m.
• Instructor: Mark Santolucito
  CULPA: 1 h-index: 8 Info
• 3 points