Hold that thought! consider finishing all 3 text GPT courses before posting questions here

Having recently completed viewing the videos for Prompt Engineering, Building Systems, and LangChain, my recommendation is to work through them in that order, though if you’re completely new to generative text AI and Large Language Models, watch the first portion ( especially the first ~ 5 minutes) of the L1 Language Models, the Chat Format and Tokens video of Building Systems before watching Prompt Engineering. And do all 3 of them before you spend too much time digging into why the examples in Prompt Engineering do or do not do something in a particular way.

For me at least, the LangChain package abstracts and extends concepts and capabilities introduced in the Building Systems course, and thus is best viewed 3rd even though it was released 2nd and appears 2nd on the Short Course menu. For example, the idea of ‘chaining’ prompts is introduced in Building Systems. The Building Systems course, with the exception of the useful ‘How it works’ section, builds on the more basic prompts and strategies introduced in Prompt Engineering.

The reason I recommend all 3 at a go, before spending too much time asking questions about the Prompt Engineering course right away, is that lots of the questions asked in this forum when the course first came out are addressed directly in the other two classes. The three stand together much better than any of them stand alone.

My 2 cents

Hi @ai_curious

I agree, “DeepLearning.AI Short Courses” could have been grouped to one group, while the “How Diffusion Models Work” could be a separate group (even though it touches on text-to-image). It’s not a big deal, but a simple structure like this could be a benefit to new comers:

  1. LLM prompting:
    1.1. ChatGPT Prompt Engineering for Developers
    1.2. Building Systems with the ChatGPT API
    1.3. LangChain for LLM Application Development
  2. Vision:
    2.1. How Diffusion Models Work

Cheers

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