I have a degree in marketing and am currently pursuing a master's in digital business and AI management, but I'm not finding it as fulfilling as I expected. I've recently become very interested in AI agents—what they do, how they're built, and how they work with large language models. I have some basic programming and general AI knowledge, but not enough to build systems confidently. I'd like to learn from the ground up in an efficient way, ideally becoming employable in this area within the next six to nine months. What topics, tools, projects, and learning steps would you recommend?
2 Answers
Build projects rather than spending months only watching tutorials. Start with something small, such as a program that collects information, summarizes text, or answers questions from a limited set of documents. Break it into steps and improve it as you learn. You’ll run into problems, but solving those problems will teach you much faster than passive study. Also learn Git early and use it for every project, since version control is expected in most real-world development roles.
Try not to learn every AI topic at the same time. Start with Python fundamentals, especially functions, classes, and working with data. Then learn how HTTP requests and APIs work, using libraries such as requests. That gives you the foundation for connecting Python programs to language models. After that, build a small project that calls an AI API and does something practical. A lot of so-called agent behavior is really a combination of prompts, tool calls, and straightforward conditional logic, so building early will help make the concepts much less mysterious.
Thanks, this is really helpful. I’ll start with Python and APIs instead of trying to tackle everything at once.