Getting Started
1. Python Fundamentals
2. Machine Learning Basics
- Recommended: Andrew Ng’s ML course
- Key concepts: Supervised learning, unsupervised learning, evaluation metrics
3. Deep Learning Introduction
- Recommended framework: PyTorch (more intuitive) or TensorFlow
- Practice projects: Digit recognition, image classification
Advanced Topics
4. Large Language Models (LLMs)
- Understand Transformer architecture
- Learn Prompt Engineering
- Try various APIs
5. AI Application Development
- Build RAG applications
- Learn Agent development
- Understand MCP protocol
Recommended Resources