Open-University Challenge by Adobe: Build a model which, within the first 90 days of the course beginning, predicts which students will not pass (withdraw and fail) when the course finishes.

Background Given this dataset from the Open University, you’ve been tasked with utilizing it to improve outcomes. https://files.acrobat.com/a/preview/a93d53df-551d-4416-b5b3-20f482d79d43

Your Assignment • Build a model which, within the first 90 days of the course beginning, predicts which students will not pass (withdraw and fail) when the course finishes. • Leverage whichever systems or programming languages you feel most comfortable using to get the job done. • Demonstrate that your prediction approach is robust by explaining or showing each of the following: o Which model you selected o Which features were included o How the model was validated o The results of the validation o The overall performance of the model • Provide your response in a PowerPoint or Word document.

Note: While we appreciate highly performant/accurate models, you will impress us more by exhibiting good practices, rational decisions, and proper techniques in your approach.

Suggestions to get started…

1. Quickly familiarize yourself with the various data available to you
2. Locate the variable that you want to predict (failures and withdrawals).
3. Identify features that you want to use to make your prediction, including features which may need to be engineered.
4. Transform your data so that it can be ingested into your model.
5. Train, tune, and validate your model. Iterate if time allows.
6. Summarize your work and results.