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Databusters: The Data Science and Economics Challenge

GitHub Repository Instructions

  • The forked repository is public by default and it can't be made private. If you wish to collaborate on the project through GitHub, you can create a private repository and add your teammates as collaborators.
  • Here is a set of instructions to create a private mirror of the repository.

Alternatively, after forking your repository, you can choose to collaborate on the project via Google CoLab.

  1. Go to https://colab.research.google.com/.
  2. Click on Open notebook > Github.
  3. Copy the link of your submission notebook eg https://github.com/dsesc-acads/Databusters/blob/main/NUS_DSESC_DATABUSTERS_TEAMNAME.ipynb
  4. Colab should be able to search for the correct notebook in github and you can click to open it.
  5. Add members by sharing the link (similar to google docs) to collaborate on the project.
  6. Under Runtime > Change runtime type, you can choose whether your code is running in R / Python (Stata is unavailable in CoLab).
  7. After completing the project, click on File > Save. You will be prompted to select your repository and branch to save in, after which the modified submission notebook will be saved in your repository.

Submission Instructions

  • Rename the submission notebook as "NUS_DSESC_DATABUSTERS_XX.ipynb". For example, if your team name is "TEAM 01", your submission notebook should be named as "NUS_DSESC_DATABUSTERS_01.ipynb".
  • You are allowed to modify the template in the submission notebook, but remember to ensure that your codes run. In the event that your code does not run, we may return it to you for amendments, but there may be penalties given.
  • Your codes can be in either R, Python or Stata.
  • You are encouraged to keep your repository private until the final submission, after which you will share the repository link with us.
  • NOTE: Use of Generative AI in your code must be declared (in your report). You are allowed to use AI for refining code or improving writing, but analysis should not be done solely on AI. Failure to do so will result in penalties.

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