Semester 1 Overview¶

Welcome to the Semester 1 knowledge base! This semester focuses on building strong foundations in mathematics, statistics, and core machine learning concepts.

🎯 Semester Goals¶

The first semester is designed to:

• Establish mathematical foundations essential for ML
• Understand deep learning architectures and training
• Master statistical methods for data analysis
• Learn fundamental machine learning algorithms and techniques

📚 Course List¶

Core Courses¶

📈 Learning Path¶

graph TD
    A[Mathematical Foundations] --> B[Statistical Methods]
    A --> C[Machine Learning]
    B --> C
    C --> D[Deep Neural Networks]
    A --> D

🎓 Key Concepts¶

This semester covers several interconnected areas:

1. Mathematical Foundations: The language of ML
2. Statistical Methods: Understanding data and uncertainty
3. Machine Learning: Core algorithms and techniques
4. Deep Learning: Advanced neural network architectures

📖 Quick Links¶

• Mathematical Foundations
• Deep Neural Networks
• Statistical Methods
• Machine Learning

📝 Blogs & Good Reads¶

🎯 Must-Read Collections¶

Navigate to individual course pages to explore detailed content, notes, and resources.