If it's the former - skip the math and start calling APIs. OpenAI, Anthropic, or open-source models via Replicate. Spend a week building something real: add a chatbot to your product, build a document Q&A system, whatever solves an actual problem.
Focus on prompt engineering, handling token limits, streaming responses, managing costs, error handling. These are the 80% of "AI development" for application builders.
The deep learning theory? You can learn that later if you actually need to fine-tune models or optimize inference. Most developers never do. Don't let the AI hype convince you that you need a PhD to ship useful AI features.
If it's the former - skip the math and start calling APIs. OpenAI, Anthropic, or open-source models via Replicate. Spend a week building something real: add a chatbot to your product, build a document Q&A system, whatever solves an actual problem.
The deep learning theory? You can learn that later if you actually need to fine-tune models or optimize inference. Most developers never do. Don't let the AI hype convince you that you need a PhD to ship useful AI features.
My second class is on to go agentic AI (calling AI from a program).
I recently attended a short presentation on RAG (ask Chat GPT). This filled in a lot of holes in my brain about LLMs.