Machine Learning Foundations / Module 02: Your first prediction experiment
All files contain fictional learning data. Keep an untouched source copy.
1. Extract practice_pack.zip to a new folder on your own device.
2. Read data_dictionary.txt and attempt learner_worksheet.txt.
3. For code tasks, use Python 3.12.14 in a local virtual environment. macOS: python3 -m venv .venv then source .venv/bin/activate. Windows: py -m venv .venv then .venv\Scripts\activate.
4. If requirements.txt is present: python -m pip install -r requirements.txt. This is your local environment; no automatic installation is performed by the website.
5. Rename the selected downloaded .py.txt reference copy to .py. Do not rename the learner scaffold as the worked script.
6. Command: python pilot_reference.py
7. Keep the reference separate from your own implementation. Compare worked_solutions.txt only after attempting the exercises.
8. Commands write only to a NEW requested output path. For a rerun choose run-02 or experiment-02.json. No uploads, website login, hosting database or live service is needed.
9. The worked_reference.html is a static offline lesson reference; it does not execute Python, install software, save progress or refresh from adjacent files.
Payments, public registration and new paid enrolment remain disabled. Paid lesson files require existing approved course access on the website. No certificate or career outcome is promised.