Farid, honestly you don't need all six of those disciplines to start. For what you're building, it mostly comes down to one thing: knowledge graphs plus RAG. That's the combination that lets an AI find the right piece of your logic under the right market conditions, which is exactly what you described wanting. The single most useful resource for your goal is DeepLearning.AI and Neo4j's short course "Knowledge Graphs for RAG" (on Coursera). It's practical and teaches precisely the retrieval problem you named: storing your ICT concepts with their relationships, not just as loose text, so the system pulls the correct model when the conditions match. Class Central also lists several free RAG courses (LangChain, LlamaIndex, DeepLearning.AI) if you want more. One honest note. The hardest part won't be storing or retrieving the knowledge. It will be the rules that connect a chart observation to a specific trade model: "when I see X on the chart, apply model Y." ChatGPT's "execution-grade" output tends to make that step sound more solved than it is. Get that mapping right and the rest follows. Happy to point you further if you get stuck there, it's the kind of thing I work on.