Course Modules

Welcome

Welcome
Module Completed Module In Progress Module Locked
Welcome 20738  
  • Page
    Course Overview & Syllabus Course Overview & Syllabus
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  • Page
    Primer Primer
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  • Page
    Hacking Resources Hacking Resources
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  • Page
    About Your Instructor About Your Instructor
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  • Page
    Coding Support (optional self-learning material) Coding Support (optional self-learning material)
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Project Guidelines

Project Guidelines
Module Completed Module In Progress Module Locked
Project Guidelines 38447  
  • Attachment
    Project Proposal Guideline - Data Section Project Proposal Guideline - Data Section
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  • Attachment
    Project Proposal Guideline - Analytics Section Project Proposal Guideline - Analytics Section
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  • Page
    Cambridge Civic Challenge Inventory Cambridge Civic Challenge Inventory
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  • Attachment
    Applied Data Science Final Report Guideline.pdf Applied Data Science Final Report Guideline.pdf
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Session 1: Making Sense of Urban Data Science

Session 1: Making Sense of Urban Data Science
Module Completed Module In Progress Module Locked
Session 1: Making Sense of Urban Data Science 28960  
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    Session 1 Recording Session 1 Recording
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  • Attachment
    11S187/11S954_20FA_lecture_note_01.pdf 11S187/11S954_20FA_lecture_note_01.pdf
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  • Context Module Sub Header
    Recommended Readings
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  • Attachment
    Townsend, A. (2015). Cities of data: Examining the new urban science. Public Culture, 27(2 (76)), 201-212 Townsend, A. (2015). Cities of data: Examining the new urban science. Public Culture, 27(2 (76)), 201-212
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  • Attachment
    Koonin, S. E., & Holland, M. (2014). The value of big data for urban science. Privacy, Big Data, and the Public Good: Frameworks for Engagement, 1, 137-152 Koonin, S. E., & Holland, M. (2014). The value of big data for urban science. Privacy, Big Data, and the Public Good: Frameworks for Engagement, 1, 137-152
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Session 2: Computing Urban Data

Session 2: Computing Urban Data
Module Completed Module In Progress Module Locked
Session 2: Computing Urban Data 28961  
  • Page
    Session 2 Recording Session 2 Recording
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  • Attachment
    11S187_20FA_lecture_note_02.pdf 11S187_20FA_lecture_note_02.pdf
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  • Context Module Sub Header
    Data Science Workshop: Intro to Python and Jupyter Notebook
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  • Attachment
    DS-workshop-2.zip DS-workshop-2.zip
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  • Context Module Sub Header
    Optional Readings
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  • Attachment
    Zheng, Y., Capra, L., Wolfson, O., & Yang, H. (2014). Urban computing: concepts, methodologies, and applications. ACM Transactions on Intelligent Systems and Technology, 5(3), 38 Zheng, Y., Capra, L., Wolfson, O., & Yang, H. (2014). Urban computing: concepts, methodologies, and applications. ACM Transactions on Intelligent Systems and Technology, 5(3), 38
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  • Attachment
    Glaeser, E. L., Kominers, S. D., Luca, M., & Naik, N. (2018). Big data and big cities: The promises and limitations of improved measures of urban life. Economic Inquiry, 56(1), 114-137 Glaeser, E. L., Kominers, S. D., Luca, M., & Naik, N. (2018). Big data and big cities: The promises and limitations of improved measures of urban life. Economic Inquiry, 56(1), 114-137
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Session 3: Instrumentation of Urban Systems

Session 3: Instrumentation of Urban Systems
Module Completed Module In Progress Module Locked
Session 3: Instrumentation of Urban Systems 28962  
  • Page
    Session 3 Recording Session 3 Recording
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  • Attachment
    11S187_20FA_lecture_note_03.pdf 11S187_20FA_lecture_note_03.pdf
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  • Context Module Sub Header
    Release: Project proposal guideline (data section)
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  • Context Module Sub Header
    Readings
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  • External Url
    Smart and Connected Communities, National Science Foundation Smart and Connected Communities, National Science Foundation
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  • Context Module Sub Header
    Data Science Workshop: Data Acquisition and Inspection
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  • Attachment
    DS Workshop notebook 3 - Data Acquisition.ipynb DS Workshop notebook 3 - Data Acquisition.ipynb
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Session 4: Cities as Cybersocial Systems

Session 4: Cities as Cybersocial Systems
Module Completed Module In Progress Module Locked
Session 4: Cities as Cybersocial Systems 28963  
  • Page
    Session 4 Class Recording Session 4 Class Recording
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  • Attachment
    Lecture_note_04.pdf Lecture_note_04.pdf
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  • Context Module Sub Header
    Readings
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  • Attachment
    Dong, L., Ratti, C., & Zheng, S. (2019). Predicting neighborhoods’ socioeconomic attributes using restaurant data. Proceedings of the National Academy of Sciences, 116(31), 15447-15452 Dong, L., Ratti, C., & Zheng, S. (2019). Predicting neighborhoods’ socioeconomic attributes using restaurant data. Proceedings of the National Academy of Sciences, 116(31), 15447-15452
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  • Context Module Sub Header
    Data Science Workshop: Data Manipulation and Description
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  • Attachment
    DS-workshop-4 (in-class).zip DS-workshop-4 (in-class).zip
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  • Attachment
    Notebook 4 - Data integration and manipulation (full version).ipynb Notebook 4 - Data integration and manipulation (full version).ipynb
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Session 5: Spatial Data in Cities

Session 5: Spatial Data in Cities
Module Completed Module In Progress Module Locked
Session 5: Spatial Data in Cities 28964  
  • Page
    Session 5 Class Recording Session 5 Class Recording
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  • Attachment
    Lecture_note_05.pdf Lecture_note_05.pdf
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  • Context Module Sub Header
    Readings
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  • External Url
    Strava, Popular with Cyclists and Runners, Wants to Sell Its Data to Urban Planners. The Wall Street Journal. 2014 Strava, Popular with Cyclists and Runners, Wants to Sell Its Data to Urban Planners. The Wall Street Journal. 2014
    Score at least   Must score at least   to complete this module item Scored at least   Module item has been completed by scoring at least   View Must view in order to complete this module item Viewed Module item has been viewed and is complete Mark done Must mark this module item done in order to complete Marked done Module item marked as done and is complete Contribute Must contribute to this module item to complete it Contributed Contributed to this module item and is complete Submit Must submit this module item to complete it Submitted Module item submitted and is complete
  • Context Module Sub Header
    Data Science Workshop: Spatial data in GeoPandas
    Score at least   Must score at least   to complete this module item Scored at least   Module item has been completed by scoring at least   View Must view in order to complete this module item Viewed Module item has been viewed and is complete Mark done Must mark this module item done in order to complete Marked done Module item marked as done and is complete Contribute Must contribute to this module item to complete it Contributed Contributed to this module item and is complete Submit Must submit this module item to complete it Submitted Module item submitted and is complete
  • Attachment
    DS-workshop-5.zip DS-workshop-5.zip
    Score at least   Must score at least   to complete this module item Scored at least   Module item has been completed by scoring at least   View Must view in order to complete this module item Viewed Module item has been viewed and is complete Mark done Must mark this module item done in order to complete Marked done Module item marked as done and is complete Contribute Must contribute to this module item to complete it Contributed Contributed to this module item and is complete Submit Must submit this module item to complete it Submitted Module item submitted and is complete
  • Attachment
    Notebook 5 - Handling Spatial Data in GeoPandas (Full notebook).ipynb Notebook 5 - Handling Spatial Data in GeoPandas (Full notebook).ipynb
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  • Attachment
    Workshop-5-Challenge with Answers.ipynb Workshop-5-Challenge with Answers.ipynb
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Session 6: Analyzing Multidimensional Urban Phenomena

Session 6: Analyzing Multidimensional Urban Phenomena
Module Completed Module In Progress Module Locked
Session 6: Analyzing Multidimensional Urban Phenomena 28965  
  • Page
    Session 6 Class Recording Session 6 Class Recording
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  • Attachment
    Lecture_note_06.pdf Lecture_note_06.pdf
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  • Context Module Sub Header
    Readings
    Score at least   Must score at least   to complete this module item Scored at least   Module item has been completed by scoring at least   View Must view in order to complete this module item Viewed Module item has been viewed and is complete Mark done Must mark this module item done in order to complete Marked done Module item marked as done and is complete Contribute Must contribute to this module item to complete it Contributed Contributed to this module item and is complete Submit Must submit this module item to complete it Submitted Module item submitted and is complete
  • External Url
    DataKind - Creating Safer Streets Through Data Science DataKind - Creating Safer Streets Through Data Science
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  • External Url
    Airbnb and New York City Reach a Truce on Home-Sharing Data Airbnb and New York City Reach a Truce on Home-Sharing Data
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  • Context Module Sub Header
    Data Science Workshop: High-Dimensional Data
    Score at least   Must score at least   to complete this module item Scored at least   Module item has been completed by scoring at least   View Must view in order to complete this module item Viewed Module item has been viewed and is complete Mark done Must mark this module item done in order to complete Marked done Module item marked as done and is complete Contribute Must contribute to this module item to complete it Contributed Contributed to this module item and is complete Submit Must submit this module item to complete it Submitted Module item submitted and is complete
  • Attachment
    DS_Workshop-6.zip DS_Workshop-6.zip
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  • Attachment
    Notebook 6 - Exploring Airbnb Data (Full notebook).ipynb Notebook 6 - Exploring Airbnb Data (Full notebook).ipynb
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Session 7: Data-Driven Urban Decision-Making and Operations

Session 7: Data-Driven Urban Decision-Making and Operations
Module Completed Module In Progress Module Locked
Session 7: Data-Driven Urban Decision-Making and Operations 28966  
  • Page
    Session 7 Class Recording Session 7 Class Recording
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  • Attachment
    Lecture_note_07.pdf Lecture_note_07.pdf
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  • Context Module Sub Header
    Readings
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  • External Url
    How Data-driven is Your City? HKS Ash Center (3 min read) How Data-driven is Your City? HKS Ash Center (3 min read)
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  • External Url
    Lai, Y., Yeung, W., & Celi, L. A. (2020). Urban Intelligence for Pandemic Response. JMIR public health and surveillance, 6(2), e18873. Lai, Y., Yeung, W., & Celi, L. A. (2020). Urban Intelligence for Pandemic Response. JMIR public health and surveillance, 6(2), e18873.
    Score at least   Must score at least   to complete this module item Scored at least   Module item has been completed by scoring at least   View Must view in order to complete this module item Viewed Module item has been viewed and is complete Mark done Must mark this module item done in order to complete Marked done Module item marked as done and is complete Contribute Must contribute to this module item to complete it Contributed Contributed to this module item and is complete Submit Must submit this module item to complete it Submitted Module item submitted and is complete
  • Context Module Sub Header
    Optional Readings
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  • External Url
    Tracking Boston’s Progress with Just One Number Tracking Boston’s Progress with Just One Number
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  • External Url
    5 Lessons from the Best Data-driven Cities. Bloomberg Cities (7 min read) 5 Lessons from the Best Data-driven Cities. Bloomberg Cities (7 min read)
    Score at least   Must score at least   to complete this module item Scored at least   Module item has been completed by scoring at least   View Must view in order to complete this module item Viewed Module item has been viewed and is complete Mark done Must mark this module item done in order to complete Marked done Module item marked as done and is complete Contribute Must contribute to this module item to complete it Contributed Contributed to this module item and is complete Submit Must submit this module item to complete it Submitted Module item submitted and is complete
  • Context Module Sub Header
    Data Science Workshop: Time-series Data
    Score at least   Must score at least   to complete this module item Scored at least   Module item has been completed by scoring at least   View Must view in order to complete this module item Viewed Module item has been viewed and is complete Mark done Must mark this module item done in order to complete Marked done Module item marked as done and is complete Contribute Must contribute to this module item to complete it Contributed Contributed to this module item and is complete Submit Must submit this module item to complete it Submitted Module item submitted and is complete
  • Attachment
    DS-workshop-7.zip DS-workshop-7.zip
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  • Attachment
    Notebook 7 - Time-series Analysis (Full notebook).ipynb Notebook 7 - Time-series Analysis (Full notebook).ipynb
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Session 8: Mid-Point Project Review

Session 8: Mid-Point Project Review
Module Completed Module In Progress Module Locked
Session 8: Mid-Point Project Review 28967  
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    Session 8 Class Recording Session 8 Class Recording
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  • Attachment
    meeting_saved_chat.txt meeting_saved_chat.txt
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Session 9: Responsible Data Science for Cities

Session 9: Responsible Data Science for Cities
Module Completed Module In Progress Module Locked
Session 9: Responsible Data Science for Cities 28968  
  • Page
    Session 9 Class Recording Session 9 Class Recording
    Score at least   Must score at least   to complete this module item Scored at least   Module item has been completed by scoring at least   View Must view in order to complete this module item Viewed Module item has been viewed and is complete Mark done Must mark this module item done in order to complete Marked done Module item marked as done and is complete Contribute Must contribute to this module item to complete it Contributed Contributed to this module item and is complete Submit Must submit this module item to complete it Submitted Module item submitted and is complete
  • Attachment
    11S187_20FA_lecture_note_09.pdf 11S187_20FA_lecture_note_09.pdf
    Score at least   Must score at least   to complete this module item Scored at least   Module item has been completed by scoring at least   View Must view in order to complete this module item Viewed Module item has been viewed and is complete Mark done Must mark this module item done in order to complete Marked done Module item marked as done and is complete Contribute Must contribute to this module item to complete it Contributed Contributed to this module item and is complete Submit Must submit this module item to complete it Submitted Module item submitted and is complete
  • Context Module Sub Header
    Readings
    Score at least   Must score at least   to complete this module item Scored at least   Module item has been completed by scoring at least   View Must view in order to complete this module item Viewed Module item has been viewed and is complete Mark done Must mark this module item done in order to complete Marked done Module item marked as done and is complete Contribute Must contribute to this module item to complete it Contributed Contributed to this module item and is complete Submit Must submit this module item to complete it Submitted Module item submitted and is complete
  • External Url
    New York City Automated Decision Systems Task Force New York City Automated Decision Systems Task Force
    Score at least   Must score at least   to complete this module item Scored at least   Module item has been completed by scoring at least   View Must view in order to complete this module item Viewed Module item has been viewed and is complete Mark done Must mark this module item done in order to complete Marked done Module item marked as done and is complete Contribute Must contribute to this module item to complete it Contributed Contributed to this module item and is complete Submit Must submit this module item to complete it Submitted Module item submitted and is complete
  • Context Module Sub Header
    Optional
    Score at least   Must score at least   to complete this module item Scored at least   Module item has been completed by scoring at least   View Must view in order to complete this module item Viewed Module item has been viewed and is complete Mark done Must mark this module item done in order to complete Marked done Module item marked as done and is complete Contribute Must contribute to this module item to complete it Contributed Contributed to this module item and is complete Submit Must submit this module item to complete it Submitted Module item submitted and is complete
  • External Url
    Why the Bronx Burned Why the Bronx Burned
    Score at least   Must score at least   to complete this module item Scored at least   Module item has been completed by scoring at least   View Must view in order to complete this module item Viewed Module item has been viewed and is complete Mark done Must mark this module item done in order to complete Marked done Module item marked as done and is complete Contribute Must contribute to this module item to complete it Contributed Contributed to this module item and is complete Submit Must submit this module item to complete it Submitted Module item submitted and is complete
  • External Url
    With Great Data Comes Great Responsibility: How Data Science Can Be Applied to Solve Public Interest Problems Without Losing Its Soul With Great Data Comes Great Responsibility: How Data Science Can Be Applied to Solve Public Interest Problems Without Losing Its Soul
    Score at least   Must score at least   to complete this module item Scored at least   Module item has been completed by scoring at least   View Must view in order to complete this module item Viewed Module item has been viewed and is complete Mark done Must mark this module item done in order to complete Marked done Module item marked as done and is complete Contribute Must contribute to this module item to complete it Contributed Contributed to this module item and is complete Submit Must submit this module item to complete it Submitted Module item submitted and is complete
  • Context Module Sub Header
    Data Science Workshop: Python Review
    Score at least   Must score at least   to complete this module item Scored at least   Module item has been completed by scoring at least   View Must view in order to complete this module item Viewed Module item has been viewed and is complete Mark done Must mark this module item done in order to complete Marked done Module item marked as done and is complete Contribute Must contribute to this module item to complete it Contributed Contributed to this module item and is complete Submit Must submit this module item to complete it Submitted Module item submitted and is complete
  • Attachment
    Notebook_09_Python Review.zip Notebook_09_Python Review.zip
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  • Attachment
    Notebook_09_Python Review (Full notebook).ipynb Notebook_09_Python Review (Full notebook).ipynb
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Session 10: Statistical Plotting

Session 10: Statistical Plotting
Module Completed Module In Progress Module Locked
Session 10: Statistical Plotting 28969  
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    Session 10 Class Recording Session 10 Class Recording
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  • Attachment
    11S187_20FA_lecture_note_10.pdf 11S187_20FA_lecture_note_10.pdf
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  • Context Module Sub Header
    Reading
    Score at least   Must score at least   to complete this module item Scored at least   Module item has been completed by scoring at least   View Must view in order to complete this module item Viewed Module item has been viewed and is complete Mark done Must mark this module item done in order to complete Marked done Module item marked as done and is complete Contribute Must contribute to this module item to complete it Contributed Contributed to this module item and is complete Submit Must submit this module item to complete it Submitted Module item submitted and is complete
  • Page
    Police Told to Give Street-Stop Data Police Told to Give Street-Stop Data
    Score at least   Must score at least   to complete this module item Scored at least   Module item has been completed by scoring at least   View Must view in order to complete this module item Viewed Module item has been viewed and is complete Mark done Must mark this module item done in order to complete Marked done Module item marked as done and is complete Contribute Must contribute to this module item to complete it Contributed Contributed to this module item and is complete Submit Must submit this module item to complete it Submitted Module item submitted and is complete
  • Context Module Sub Header
    Data Science Workshop: Statistical Plotting with Seaborn
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  • Attachment
    Notebook 10 - Statistical Plotting (In-class).ipynb Notebook 10 - Statistical Plotting (In-class).ipynb
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  • Attachment
    Notebook 10 - Statistical Plotting (Full-notebook).ipynb Notebook 10 - Statistical Plotting (Full-notebook).ipynb
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  • Attachment
    sqf-2018.xlsx sqf-2018.xlsx
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Session 11: Machine Learning for Cities - Application and Controversies

Session 11: Machine Learning for Cities - Application and Controversies
Module Completed Module In Progress Module Locked
Session 11: Machine Learning for Cities - Application and Controversies 28971  
  • Page
    Session 11 Class Recording Session 11 Class Recording
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  • Attachment
    11S187_20FA_lecture_note_11.pdf 11S187_20FA_lecture_note_11.pdf
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  • Context Module Sub Header
    Readings
    Score at least   Must score at least   to complete this module item Scored at least   Module item has been completed by scoring at least   View Must view in order to complete this module item Viewed Module item has been viewed and is complete Mark done Must mark this module item done in order to complete Marked done Module item marked as done and is complete Contribute Must contribute to this module item to complete it Contributed Contributed to this module item and is complete Submit Must submit this module item to complete it Submitted Module item submitted and is complete
  • Page
    The ethics of smart cities and urban science The ethics of smart cities and urban science
    Score at least   Must score at least   to complete this module item Scored at least   Module item has been completed by scoring at least   View Must view in order to complete this module item Viewed Module item has been viewed and is complete Mark done Must mark this module item done in order to complete Marked done Module item marked as done and is complete Contribute Must contribute to this module item to complete it Contributed Contributed to this module item and is complete Submit Must submit this module item to complete it Submitted Module item submitted and is complete
  • Page
    Why Real-Time Traffic Control Has Mobility Experts Spooked Why Real-Time Traffic Control Has Mobility Experts Spooked
    Score at least   Must score at least   to complete this module item Scored at least   Module item has been completed by scoring at least   View Must view in order to complete this module item Viewed Module item has been viewed and is complete Mark done Must mark this module item done in order to complete Marked done Module item marked as done and is complete Contribute Must contribute to this module item to complete it Contributed Contributed to this module item and is complete Submit Must submit this module item to complete it Submitted Module item submitted and is complete
  • Context Module Sub Header
    Data Science Workshop: NLTK
    Score at least   Must score at least   to complete this module item Scored at least   Module item has been completed by scoring at least   View Must view in order to complete this module item Viewed Module item has been viewed and is complete Mark done Must mark this module item done in order to complete Marked done Module item marked as done and is complete Contribute Must contribute to this module item to complete it Contributed Contributed to this module item and is complete Submit Must submit this module item to complete it Submitted Module item submitted and is complete
  • Attachment
    Notebook 11 - Unstructured data I (In-class).ipynb Notebook 11 - Unstructured data I (In-class).ipynb
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  • Attachment
    Notebook 11 - Unstructured data I (Full notebook).ipynb Notebook 11 - Unstructured data I (Full notebook).ipynb
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  • Attachment
    Cambridge_listings_2019_July.csv Cambridge_listings_2019_July.csv
    Score at least   Must score at least   to complete this module item Scored at least   Module item has been completed by scoring at least   View Must view in order to complete this module item Viewed Module item has been viewed and is complete Mark done Must mark this module item done in order to complete Marked done Module item marked as done and is complete Contribute Must contribute to this module item to complete it Contributed Contributed to this module item and is complete Submit Must submit this module item to complete it Submitted Module item submitted and is complete
  • Attachment
    Cambridge_listings_2019_September.csv Cambridge_listings_2019_September.csv
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  • Attachment
    Cambridge_listings_2019_August.csv Cambridge_listings_2019_August.csv
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Session 12: Art and Science of Cities

Session 12: Art and Science of Cities
Module Completed Module In Progress Module Locked
Session 12: Art and Science of Cities 28972  
  • Page
    Session 12 Class Recording Session 12 Class Recording
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  • Context Module Sub Header
    Reading
    Score at least   Must score at least   to complete this module item Scored at least   Module item has been completed by scoring at least   View Must view in order to complete this module item Viewed Module item has been viewed and is complete Mark done Must mark this module item done in order to complete Marked done Module item marked as done and is complete Contribute Must contribute to this module item to complete it Contributed Contributed to this module item and is complete Submit Must submit this module item to complete it Submitted Module item submitted and is complete
  • Page
    Jane Jacobs: Is There Good Science behind Urban Planning? Jane Jacobs: Is There Good Science behind Urban Planning?
    Score at least   Must score at least   to complete this module item Scored at least   Module item has been completed by scoring at least   View Must view in order to complete this module item Viewed Module item has been viewed and is complete Mark done Must mark this module item done in order to complete Marked done Module item marked as done and is complete Contribute Must contribute to this module item to complete it Contributed Contributed to this module item and is complete Submit Must submit this module item to complete it Submitted Module item submitted and is complete

Project Final Presentations

Project Final Presentations
Module Completed Module In Progress Module Locked
Project Final Presentations 28973  
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    Final Presentation Slide-Deck + Logistics + Recommendations Final Presentation Slide-Deck + Logistics + Recommendations
    Score at least   Must score at least   to complete this module item Scored at least   Module item has been completed by scoring at least   View Must view in order to complete this module item Viewed Module item has been viewed and is complete Mark done Must mark this module item done in order to complete Marked done Module item marked as done and is complete Contribute Must contribute to this module item to complete it Contributed Contributed to this module item and is complete Submit Must submit this module item to complete it Submitted Module item submitted and is complete
 
minimum score must view must submit must contribute