⚡ Level 1101: Machine Learning & AI

Welcome, aspiring AI architect! You have reached the realm of Digital Intelligence, where machines learn from data and algorithms evolve to solve complex problems. Here you will master the arts of machine learning, neural networks, and artificial intelligence.

🎯 Level Overview

📚 Learning Objectives

By completing this level, you will:

• Understand fundamental machine learning concepts and algorithms
• Master Python libraries for data science (NumPy, Pandas, Scikit-learn)
• Build and train neural networks using TensorFlow and PyTorch
• Implement natural language processing solutions
• Develop computer vision applications
• Deploy ML models to production using MLOps practices
• Apply ethical AI principles in your projects

🗺️ Quest Map

graph TB
    subgraph "Level 1101: Machine Learning & AI"
        ML[ML Fundamentals]
        PY[Python for Data Science]
        NN[Neural Networks]
        DL[Deep Learning Frameworks]
        NLP[Natural Language Processing]
        CV[Computer Vision]
        MLOPS[MLOps Engineering]
        ETHICS[AI Ethics]
    end
    
    subgraph "Prerequisites (Level 1100)"
        DE[Data Engineering]
    end
    
    subgraph "Unlocks (Level 1110)"
        ARCH[Architecture & Design]
    end
    
    DE --> ML
    DE --> PY
    ML --> NN
    PY --> NN
    NN --> DL
    DL --> NLP
    DL --> CV
    NLP --> MLOPS
    CV --> MLOPS
    MLOPS --> ARCH
    ML --> ETHICS

📋 Available Quests

🎮 Recommended Quest Order

1. Foundation Track (Start Here)
   • Python for Data Science → ML Fundamentals → AI Ethics
2. Deep Learning Track
   • Neural Networks → Deep Learning Frameworks
3. Application Track
   • Natural Language Processing → Computer Vision
4. Production Track
   • MLOps Engineering

🛠️ Required Tools & Technologies

• Languages: Python 3.9+
• ML Libraries: Scikit-learn, NumPy, Pandas
• Deep Learning: TensorFlow, PyTorch
• NLP: Hugging Face Transformers, NLTK, spaCy
• Computer Vision: OpenCV, PIL
• MLOps: Docker, MLflow, Kubernetes
• Environment: Jupyter Notebooks, VS Code

📈 Skill Progression

Data Engineering (1100) → Machine Learning → AI Applications → Production ML
                           │                    │
                           ├── Supervised Learning
                           ├── Unsupervised Learning
                           ├── Deep Learning ──────┤
                           └── Reinforcement       ├── NLP
                               Learning            ├── Computer Vision
                                                   └── Generative AI

🎯 Level Completion Criteria

To advance to Level 1110 (Architecture & Design), you must:

• Complete at least 5 quests in this level
• Build a working ML model from scratch
• Deploy an ML model to production
• Demonstrate understanding of AI ethics principles
• Earn minimum 1,000 XP in this level

🔗 Related Resources

• Level 1100: Data Engineering
• Level 1110: Architecture & Design
• Data Scientist Path

“The measure of intelligence is the ability to change.” — Albert Einstein

Ready to teach machines? Begin your journey into AI! 🤖