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Syllabus 📖

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Table of contents

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About CE3201

This course aims to introduce basic data science concepts and visualization techniques to students who are interested in climate, buildings, environment, etc. Students will gain hands-on experience in terms of how to mine, model and visualize data to tell a compelling story of global challenges (e.g., emerging climate crisis).

Learning Outcomes

  • An understanding of visualization techniques including data models, graphical perception and methods for visual encoding and interaction.
  • Exposure to several common data domains and corresponding analysis tasks, including multivariate data, networks, text and cartography.
  • Practical experience building visuals from data using open-source tools and libraries, and deriving sound interpretations from them.

Prerequisites

This module requires no prior knowledge of progamming. Only basic concepts of statistics are required.

Hybrid Format

CE3201 will be taught in a hybrid format with lectures and tutorials. For the most up-to-date schedule, you can check the [Home]({{ site.baseurl }}{% link index.md %}) page.

Lectures

  • We will have 6 lectures in total. One lecture per week.
  • These lectures will be split into two themes. The first three will focus on data analysis, which will be followed by another three lectures on data visualization.

Tutorials

  • We will have 6 tutorials in total. One tutorial per week.
  • Tutorials are prepared in Jupyter Notebook format and are fully available online.
  • We understand that sometimes programming and debugging could be cumbersome. So please come to the computer lab to do tutorials so that the TAs and I can provide hands-on help.
  • You are welcome to seek help during office hours or through emails. But the best place to get help is the weekly tutorial session.

Office Hours

  • Weekly fixed office hours can be found on the [Schedule]({{ site.baseurl }}{% link schedule.md %}) tab, and will be held either virtually or in-person depending on your needs.
  • I have an open-door policy. So feel free to drop by my office for any reason, including course material clarification, questions on tutorials, assignments, and projects, or even just to hang out.

Textbooks and Materials

  • Primary textbook: pyCIVIL (python ClImate VIsuaLs), a free online textbook that is currently under development. Your comments and suggestions are welcome.
  • Supplementary textbook: Fundamentals of Data Visualization. (free online book; although based on R, it is a great guide to make fabulous visualizations that correctly reflect the data).
  • A computer.
  • Stable internet connection.

Grading Scheme

Assignment type Weight Number
Tutorial attendance1 20% 4 (+2)2
Homework 35% 2
Final Project 45% 1

Footnotes

  1. Please come to the computer lab (PC5 & PC6) on time to do tutorials. Attendance will be checked. ↩

  2. There are 6 tutorial sessions in total, but you can miss Tutorial 4 (Oct 30, Week 11) and Tutorial 6 (Nov 13, Week 13) and still receive full points. ↩