🎯 Learning Roadmap Flutter App

A Flutter app to track your progress in learning Attention + Time Series for tabular imputation research (ICML 2026 goal).

📱 Features

• ✅ Checkboxes for each learning item
• 💾 Persistent storage - your progress is saved automatically
• 📊 Progress tracking - see overall and per-level progress
• ⭐ Important items highlighted - never miss the key concepts
• 🔗 Resource links - quick access to tutorials and papers
• 🌙 Dark mode support - easy on the eyes
• 📱 Mobile-friendly - works on iOS, Android, and Web

🖼️ Screenshots

┌─────────────────────────────┐
│     Learning Roadmap        │
│   Attention + Time Series   │
│                             │
│  Overall Progress           │
│  ████████░░░░░░░ 45/100     │
│                             │
│  ▼ Level 0 - Prerequisites  │
│    ████████░░░ 80%          │
│                             │
│  ▼ Level 1 - ML Basics      │
│    ██████░░░░ 60%           │
│                             │
│  ► Level 2 - Deep Learning  │
│    ░░░░░░░░░░ 0%            │
│                             │
└─────────────────────────────┘

🚀 Getting Started

Prerequisites

1. Install Flutter: https://docs.flutter.dev/get-started/install
2. Verify installation:

   flutter doctor

Installation

1. Create a new Flutter project (or use this as a starting point):

   flutter create learning_roadmap
   cd learning_roadmap

2. Replace files:

   • Replace lib/main.dart with the provided main.dart
   • Replace pubspec.yaml with the provided pubspec.yaml

3. Get dependencies:

   flutter pub get

4. Run the app:

   # For web
   flutter run -d chrome
   
   # For mobile (with connected device/emulator)
   flutter run
   
   # For desktop
   flutter run -d windows  # or macos, linux

📁 Project Structure

learning_roadmap/
├── lib/
│   └── main.dart         # Main app code (all in one file for simplicity)
├── pubspec.yaml          # Dependencies
└── README.md             # This file

🎮 How to Use

1. Open the app - you'll see all 8 levels collapsed
2. Tap a level to expand it and see sections
3. Tap checkboxes to mark items as complete
4. Look for ⭐ stars - these are the most important items
5. Tap 🔗 link icons to see resource URLs
6. Track progress - watch the progress bars fill up!

📚 Learning Levels

Level	Topic	Duration
0	Prerequisites (Math + Python)	2-4 weeks
1	Machine Learning Basics	3-4 weeks
2	Deep Learning Fundamentals	3-4 weeks
3	Sequence Models (RNN, LSTM)	2 weeks
4	Attention & Transformers ⭐	3-4 weeks
5	Time Series Specific	2-3 weeks
6	Research Papers	4-6 weeks
7	Start Your Research!	Ongoing

🔧 Customization

Adding New Items

Edit the RoadmapData.getLevels() method in main.dart:

LearningItem(
  id: 'unique_id',           // Must be unique
  title: 'Item title',
  description: 'Optional description',
  url: 'https://...',        // Optional link
  isImportant: true,         // Show star icon
),

Changing Colors

Each level has a color defined:

color: Colors.purple,  // Change to any Material color

Resetting Progress

Clear the app data, or add a reset button:

// Add this method to _RoadmapScreenState
Future<void> _resetProgress() async {
  final prefs = await SharedPreferences.getInstance();
  await prefs.remove('completed_items');
  setState(() {
    completedItems.clear();
    _applyCompletedItems();
  });
}

📦 Dependencies

• shared_preferences - For saving progress locally
• url_launcher - For opening links (optional)
• cupertino_icons - For iOS-style icons

🌐 Web Deployment

To build for web:

flutter build web

Then deploy the build/web folder to any static hosting (GitHub Pages, Vercel, Netlify, etc.).

📱 Mobile Deployment

For Android APK:

flutter build apk

For iOS:

flutter build ios

🤝 Contributing

Feel free to customize this roadmap for your own learning journey! You can:

• Add new topics
• Modify the learning path
• Add more resources
• Improve the UI

📄 License

MIT License - feel free to use and modify!

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Good luck on your ICML 2026 journey! 🚀

Made with ❤️ for aspiring ML researchers