What’s the best way to learn Python and build AI agents from scratch?

Try not to learn the entire AI ecosystem at once. Start with Python fundamentals, especially functions, classes, error handling, and working with files. Then learn how HTTP requests and APIs work using libraries such as requests. That gives you the foundation to interact with language models programmatically.

After that, build small projects instead of only watching tutorials. For example, make a script that sends text to an API and summarizes or classifies the response. Many beginner-level “agents” are essentially an LLM combined with prompts, tool calls, and straightforward conditional logic, so building something small will make the concepts much less mysterious.

Use project-based learning from the beginning. Pick one manageable idea, such as an assistant that retrieves information, summarizes documents, or processes structured data, and develop it one step at a time. You’ll learn faster by solving the problems that come up than by passively completing course after course.

Also learn Git early and keep your projects in organized repositories. For an entry-level job, being able to show working projects and explain your code can matter as much as knowing a particular AI framework. A practical progression would be Python, APIs and JSON, Git, basic web development, LLM APIs, retrieval and tool use, and only then more specialized agent frameworks.