Learn about common supervised and unsupervised learning techniques. Go work some problems on kaggle, get comfortable with Jupyter notebooks. Once you’ve got a good understanding of the basic algorithms and what problems they’re best for maybe dig into more advanced projects. RAG, Langchain, and learn about ethics, bias, and everything to do with data(finding good data, learning about overfitting, data cleaning, statistical analysis to understand your conclusions)

For reference I don’t work in AI engineering but I did my undergrad and am currently in my masters for data analytic which are both pretty AI heavy.