https://github.com/doctor-phil/econ323_2025_spring
Course materials for ECON323 Quant. Econ. Modelling and Data Science in Spring 2025
https://github.com/doctor-phil/econ323_2025_spring
Last synced: 2 months ago
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Course materials for ECON323 Quant. Econ. Modelling and Data Science in Spring 2025
- Host: GitHub
- URL: https://github.com/doctor-phil/econ323_2025_spring
- Owner: doctor-phil
- Created: 2025-01-02T18:41:44.000Z (6 months ago)
- Default Branch: main
- Last Pushed: 2025-04-08T23:00:54.000Z (2 months ago)
- Last Synced: 2025-04-09T00:18:45.885Z (2 months ago)
- Language: Jupyter Notebook
- Homepage:
- Size: 604 KB
- Stars: 4
- Watchers: 2
- Forks: 6
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Course materials for ECON323
Previous **programming experience** and classwork is useful, but **not required**. We will also talk about the applications of the econometric and statistical learning methods.
We will follow the [QuantEcon DataScience](https://datascience.quantecon.org/) textbook
## Computational Setup
Installing software on your laptop is not mandatory. Instead,
- Go to the [QuantEcon DataScience](https://datascience.quantecon.org/) website and navigate to to notebook you want to use
- To import a lecture into UBC JupyterOpen or Syzygy, click the "launch notebook" icon in the top right corner, and enter: https://open.jupyter.ubc.ca (or https://ubc.syzygy.ca) as the private server. Once we get started, it might be easier for you to install [JupyterLab](https://jupyter.org/) on your own computer.
- See [Troubleshooting](https://datascience.quantecon.org/introduction/troubleshooting.html) for how to reset notebooks, etc.
- We strongly suggest creating a GitHub account and signing up for the [GitHub Student Developer Pack](https://education.github.com/pack/)
You are also encouraged to install [Anaconda](https://www.anaconda.com/) on your machines.
If possible, please bring a laptop to class to interactively discuss the material.
## Instructor and Teaching Assistant
- Philip Solimine [[email protected]](mailto:[email protected])
- Office Hours: Tuesday/Thursday 12pm-1pm in Iona 106
- TA: Bruno Esposito [[email protected]](mailto:[email protected])
- Office Hours: 4:30pm-5:30pm Fridays in IONA 335
## Syllabus
See [Syllabus](syllabus.md) for more details
Major course sections
1. **Python Fundamentals**
2. **Scientific Computing and Economics**
3. **Introduction to Pandas and Data Wrangling**
4. **Data Science Case Studies and Tools**
Grading: Problem sets: 10%; Midterm: 30%; Final projects: 20%; Final exam: 35%; Attendance/Participation: 5%
The [final project](final_project.md) is open ended. See [previous projects](https://datascience.quantecon.org/theme/projects.html)
[Lecture and Problem Set Schedule](schedule.md)
Read the [problem set submission rules](problemsetrules.md) before attempting the problem sets. **Not following these rules will result in deducted marks.**