Many fellow engineers ask for recommendations on AI & ML tutorials. While there are fantastic resources out there, a one-size-fits-all answer can be tricky. Here’s why:

Tailored Learning: AI and ML encompass a wide array of topics. Asking for a single beginner tutorial is like asking for a tutorial on backend development—it really depends on what you're interested in: APIs, Distributed Systems, Databases, Event Driven Architectures, …?

So, if you're starting out, consider what aspect of AI & ML intrigues you the most. Are you curious about:

• High-level AI use cases?
• Foundations of ML: linear algebra and statistics?
• Leveraging AI APIs for automation?
• Tooling like Python, Pandas, PyTorch, …?
• Data preprocessing & feature engineering?
• MLOps?
• Ethical considerations and AI safety?
• Natural language processing?
• Computer vision?
• …

Understanding what you want to focus on will help you find the right resources. Feel free to reach out with specific areas you're interested in, and I’ll do my best to guide you!