D4. Documentation Plan

Documentation Plan – 3D Engagement Cube

1. Overview

The 3D Engagement Cube is a machine-learning scoring pipeline designed for a technical user at the client company.

This documentation plan summarizes what documentation will be produced, who it is for, and how it will enable the intended user to load data, configure connections, and run the model end-to-end.

Unlike a full software product, this project only delivers a model + Python pipeline, so documentation is intentionally simple and focused.

2. User Types

2.1 Technical Operator (Primary User)

• Will run the model monthly/weekly

• Comfortable with Python, virtual environments, editing config files

• Knows how to work with CSVs or AWS S3

• Needs clear instructions, not conceptual explanations

2.2 System Administrator (Secondary User)

• Sets up Python environment

• Installs dependencies

• Configures AWS credentials if needed

• Rarely interacts with code after setup

3. Documentation Deliverables

We will produce exactly two written documents and two short videos:

3.1 README.md – User Manual

This teaches the technical operator how to use the repository:

• What the project does (brief)

• Required Python version

• How to install dependencies

• How to configure local or S3 data paths

• How to run

• Where outputs appear

• Common errors and how to fix them

This is the main document the user will reference.

3.2 ADMIN_SETUP.md – Administrator Manual

This teaches the system administrator how to set up the environment:

• Supported OS versions

• Required Python version

• How to create/activate a virtual environment

• How to install dependencies

• How to configure AWS CLI (optional)

• How to verify installation

• Folder structure overview

• How to redeploy or reinstall

3.3 Videos (per course requirement)

Two Zoom-recorded walkthroughs:

1. Video 1 – Installation & Setup

   • Cloning repo

   • Creating venv

   • Installing dependencies

   • Configuring AWS credentials

   • Testing environment

2. Video 2 – Running the Model

   • Editing config file

   • Running training and scoring

   • Locating outputs

   • Validating results

Both videos will be linked in the final handoff.

4. README.md Content Breakdown

The README.md will contain:

4.1 Prerequisites

• Python version

• Install AWS CLI (if using S3)

• Install required libraries via pip

4.2 Setup Instructions

• python -m venv venv

• source venv/bin/activate or venv\Scripts\activate

• pip install -r requirements.txt

4.3 Connecting to Data

• Option A: Local CSVs

• Option B: AWS S3 (explained clearly)

4.4 Output Files

• Path: artifacts/scores/full_scores.csv

• Description of columns

5. Administrator Manual Content Breakdown

The ADMIN_SETUP.md will include:

• Supported OS versions (macOS, Ubuntu, Windows via WSL2)

• Python version requirements

• How to install AWS CLI (if needed)

• IAM credential setup

• Environment variables

• Virtual environment setup

• How to test connection to data

• File structure reference

• Steps for redeployment if environment breaks

This ensures any future administrator can reinstall or move the system.

6. Delivery Mechanisms

To align with modern software practices:

• README.md in repository root

• ADMIN_SETUP.md placed in /docs/

• FLUTTER_UI.md placed in /docs/

• Setup/tutorial video linked on website