# Data Academy Honors

A recognition program for demonstrating mastery of data science and machine learning concepts. Complete badges to earn ranks and show your expertise as a Data Detective.

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## Program Overview

**Mission:** Recognize students who go beyond the basics to demonstrate true understanding of data science concepts and their application to chemical engineering problems.

**Timeline:** Designed to be achievable within one semester

**Philosophy:** Like a detective earning credentials, each badge and rank represents demonstrated skill in investigating data, building models, and communicating findings responsibly.

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## Quick Start

1. **Complete Lectures & Quizzes** - Work through course material
2. **Earn Badges** - Demonstrate mastery in each area (see [Badges](badges.md))
3. **Achieve Ranks** - Combine badges with capstone activities (see [Ranks](ranks.md))
4. **Track Progress** - Use the tracking system to monitor your journey

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## The Five Required Badges

| Badge | Icon | Focus | Lectures |
|-------|------|-------|----------|
| **Data Wrangler** | 🔍 | Data manipulation & exploration | 01-03 |
| **Pattern Seeker** | 🗜️ | Dimensionality reduction & visualization | 04 |
| **Model Builder** | 🎯 | Regression & model selection | 05-07 |
| **Ensemble Master** | 🌲 | Ensemble methods & clustering | 08-09 |
| **Uncertainty Expert** | 📏 | UQ & interpretability | 10-11 |

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## The Four Ranks

| Rank | Requirements | Meaning |
|------|--------------|---------|
| **Data Apprentice** | 1 badge | Beginning the journey |
| **Data Analyst** | 2 badges + midterm | Foundational competence |
| **Data Scientist** | 4 badges + field experience | Working professional level |
| **Senior Data Scientist** | All 5 badges + final + project | Full mastery |

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## How It Works

### Earning Badges

Each badge requires:
1. **Quiz Performance**: Average 75%+ on section quizzes
2. **Assignments**: Complete coding assignments
3. **Badge Activity**: One hands-on activity demonstrating the skill

### Advancing Ranks

Each rank requires:
1. **Badge Count**: Accumulate required badges
2. **Exam Performance**: Meet exam thresholds
3. **Capstone Activity**: Rank-specific challenge

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## Recognition

Completed achievements are recognized through:
- **Digital Badges**: Shareable credentials
- **Course Records**: Official documentation
- **Portfolio Building**: Each badge adds to your data science portfolio

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## Files in This Directory

- `README.md` - This overview
- `badges.md` - Detailed badge requirements and activities
- `ranks.md` - Rank progression and capstone activities
- `tracking.json` - Progress tracking schema

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## Character Guides

Each badge is championed by course characters:

| Badge | Champions |
|-------|-----------|
| Data Wrangler | Nadia Null, Practice Panda |
| Pattern Seeker | Dee Dimension, Viz Vizzy |
| Model Builder | Reggie Regression, Val Validation |
| Ensemble Master | Forrest Random, Clara Cluster |
| Uncertainty Expert | Quinn Quantify, SHAP Shapley |

See [characters.md](../characters.md) for the full cast!

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*"Data doesn't lie, but it can be misunderstood. A good detective lets the data speak while questioning assumptions."*