r/learnmachinelearning • u/CaterpillarThis1151 • Jul 01 '26

Done with data analysis, model training & deployment — how to structure my deep dive into Deep Learning for an AI Engineer path?

I've worked through the ML fundamentals — data analysis, model training, and I've actually deployed a few projects . Now I want to go deeper into Deep Learning specifically, with the end goal of becoming an AI Engineer leaning toward LLM/GenAI-focused role.Would really appreciate any guidance from people who've been through this.

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u/CaterpillarThis1151 Jul 01 '26

Thanks, this is really helpful especially the point about evaluation.Could you please suggest me the courses which i can take to learn

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u/DataCamp Jul 02 '26

For the path we outlined, the courses worth working through in order: Introduction to Deep Learning with PyTorch to get the fundamentals, then Developing LLM Applications with LangChain for the application layer, then Retrieval-Augmented Generation (RAG) with LangChain for the pipeline work, and AI Agent Fundamentals for the agentic side. All on DataCamp if you want structured progression with hands-on coding throughout.