Code of Conduct
Welcome to CUSP and to Principles of Urban Informatics! Diversity is considered a resource that enriches us culturally and intellectually in this class.
I expect to see a supportive, collaborative attitude from all of you, to assure we maintain and foster a learning environment that leads to rigor, excellence, and happiness. No instances of harassment or attempts to marginalize students will be tolerated in my class. If you have concerns, if you do not feel safe or are made to feel unwelcome, please come talk to me.
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Instructors: Dr. Federica Bianco
contact: fb55 @ nyu.edu
class times:
Wed+Thu 9:30-10:55am
Thu 5:30-8:30pm

Sessions will run roughly in parallel, and you are always welcome to sit in both lectures. However, please consult me or the CAs if you need to miss your assigned session to assure that you are pointed to the corresponding lecture in the other session.
Notice that the Thursday class will run till 8:30pm, not 8:20pm as stated in the official NYU syllabus, to allow me to give you a half class break


Class Assistants:
Ilyas Habeeb: mih278 @ nyu.edu
Fu Shang: fs1520 @ nyu.edu

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  • check calendar for supplementary session
  • office hours : 370 Jay St BK room 1221:
    Dr. FBB: W12-2+M4-530/F10-12 (check first for M/F)
    IH: Tu5-630+F4-530
    FS: Tu10-12+F3-4
  • detailed syllabus coming soon Syllabus

  • Resources

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Class Description

This course will teach you the basis of data driven urban research: the major concepts, tools, and techniques for what informatics can do for cities. You will acquire basic computational skills, basic knowledge of statistical analysis, error analysis, data acquisition and management, integration, and analytics, working with large datasets and understanding data sources, ​visualization, and data science, and also includes material not usually covered in computer science courses: how to best handle spatial-temporal data, GIS, issues related to citizen science and participatory sensing, instrumentation, physical sensors, imagery, and mobile sensing platforms, issues of data ethics, privacy. After this class you should be able to formulate a question relevant to Urban Science, find appropriate data to answer the question, prepare and analyze the data, get an answer, and communicate your answer, and your confidence level in the answer.

At times you will have a hard time figuring out the solutions to problems. Remember that we admitted you because we believed you would have a positive influence on the class, and that being at CUSP can fulfill your potential as an Urban Scientist. Don't worry about how much you already know, especially do not compare it to what other students know. You may have the wrong perception of your skills, and of the skills of your classmates, and your strengths and the strength of your background may lie in another set of skills, just as important for an Urban Scientist. As you work, focus on your strengths, not your weaknesses. We are here to help you develop the skills you do not yet have and strengthen the skills you already have. You are here because we want you to be here and believe in your potential.

This course should serve as the basis for all the following classes, and your future projects. The course will be organized in a modular fashion, with guest lectures.

There are very few rules. Please do not break them! Here you can find the grading scheme, and this is the NYU statement of Academic Integrity, to which you will be strictly held.

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Class Schedule

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