What's included

• GitHub Repository

  Well-documented codebase with version control for transparency. Modular and reusable code for data cleaning, analysis, and visualization.

• Jupyter Notebooks

  Interactive notebooks showcasing key analyses, models, and visualizations. Step-by-step methodology with markdown explanations for reproducibility.

• Summary Report

  Comprehensive PDF or slide deck summarizing insights, methods, and recommendations. Executive summary highlighting key findings for non-technical stakeholders.

• Dashboards or Visualizations

  Interactive dashboards (e.g., Power BI, Tableau, or custom web apps) for ongoing data exploration. Static charts and graphs for presentations or documentation.

• Raw and Processed Flat Files

  Cleaned datasets in user-friendly formats (CSV, Excel, or SQL dumps). Documentation of transformations and assumptions.

• Statistical Models

  Trained and/or validated models with instructions for deployment or integration. Scripts for retraining and testing.

• Documentation

  Detailed readme files, user guides, and process documentation. Explanation of metrics, algorithms, and tools used.

• Consultation or Training

  Walkthrough of deliverables and insights with Q&A sessions. Training materials for internal teams to use or extend the analysis.