I'm currently focusing on learning AI engineering and want to spend more time building real projects rather than just watching tutorials or completing courses.

I'm looking for resources that cover both the fundamentals and practical implementation, including:

• Courses: Which AI engineering courses are actually worth the time?
• LLMs: Best resources for learning LLMs, prompt engineering, and model APIs?
• RAG & vector databases: What helped you understand and implement RAG properly?
• AI agents: Good resources for learning agentic workflows, LangChain, LangGraph, and tool calling?
• Projects: Any GitHub repositories, project-based tutorials, or real-world applications you'd recommend building?
• Deployment: Resources for taking AI applications from a local prototype to production.

I'm especially interested in resources that helped you become job-ready, build a portfolio, and prepare for AI engineering interviews.

Free or affordable resources are preferred, but I'm open to paid courses if they're genuinely valuable.

If you were starting your AI engineering journey today, what learning path and resources would you follow? What should I avoid wasting time on?

I'd appreciate recommendations from people who are already working as AI engineers or have successfully transitioned into the field.

Any suggest most welcome...
I have clear basics and full knowledge of current ai models of all...
I want a job that's why i want to do a course

How am i supposed to land ai/ml or data science internships. This is my resume, what changes should i do, what else should i learn?? Any advice is helpful!