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CE88 2018 Data Science for Smart Cities

Piazza bCourses

September 10

  • Introduction: Cities as complex urban systems
  • Modeling principles
  • Urban data ecosystem

Lectures 1&2

Datahub Minilab 1

Homework 1

September 17

  • Spatio-temporal nature of urban data
  • Working with Census data

Lectures 3&4

Datahub Minilab 2

Homework 2

September 24

  • Data acquisition and processing
  • APIs

Lectures 5&6

Datahub Minilab 3

Homework 3

October 1

  • Bringing together geo data
  • Modeling principles

Lectures 7&8

Datahub Minilab 4 - Geo Intro

Datahub Minilab 4 - Travel Times (upd: mapping part solutions)

Homework 4

October 8

  • Concepts of choice modeling
  • Environmental impact of travel choices

Lectures 9&10

Datahub Minilab 5 - Mode choice and VMT

Homework 5

October 15

  • Exploratory data analysis
  • How to specify a model

Lectures 11&12

Datahub Minilab 6 - Mode choice data exploration

No Homework

October 22

  • Making predicitons

Lectures 13&14

Datahub Minilab 7 - Nearest neighbor mode choice and solutions

Homework 7

October 29

  • Confidence intervals
  • Uncertainty in predictions

Lecture 15&16

Datahub Minilab 8 - CI and uncertainty (no submission required)

No Homework

Midterm

Description

Data and a starter notebook

Follow Piazza announcements: a Kaggle submissions link will be posted soon, but you can start working on the dataset right now!

November 5 - Midterm Hints!

The following minilab further helps you get started with the midterm. Submission is not required.

Taxi data minilab

November 26

  • Energy, renewables, demand and supply
  • Cluster analysis

Lecture

Datahub Minilab 11 - Energy demand and supply (submission required!)

Datahub Minilab 12 - Cluster analysis of EVs charging (optional, max of 5 bonus points)

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