AI for Power Electronics

A comprehensive learning path for applying AI in Power Electronics Design.

1. Foundational

1.1 Python Basics

• Basic Language Formats

1.2 Manage Environment and Dependencies

• Package management with pip, conda, venv

1.3 Pythonic Programming

• Python in 3 Days
• 30 Days of Python

2. Basic

2.1 Python Modules

• NumPy: Numpy Tutorials
• Pandas: Pandas Tutorial
• Scikit-learn: Sklearn Tutorial
• PyTorch: PyTorch Tutorials

2.2 Simulation Automation

• PLECS: XMLRPC Controller Design
• Simulink: Sim Command Guide
• ANSYS: PyAnsys Documentation
• LTspice: PyLTSpice Package

3. Intermediate

3.1 Meta-Heuristic Algorithms

1. Metaheuristics Library
2. PyMetaheuristic

3.2 Machine Learning

1. ML with Python
2. ML Tutorials
3. Ensemble Methods

3.3 Deep Learning

1. PyTorch Deep Learning
2. CS5242 Course

4. Advanced

4.1 Physics-informed Machine Learning

1. NVIDIA Modulus
2. Physics-Aware Neural Networks (PANN)

4.2 Generative AI for Power Electronics

1. PE-GPT: Power Electronics GPT
2. OpenAI Cookbook

4.3 Graph Neural Networks

1. Benchmarking GNNs
2. GNNs Recipe

4.4 Reinforcement Learning

1. RL Fundamentals
2. RL: An Introduction

4.5 Edge Deployment

• Awesome Edge Machine Learning