@DanKornas: Your second brain needs more than a chatbot demo second-brain-ai-assistant-course is an open-source course repo from De…

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An open-source course repository from Decoding AI that teaches builders how to create a personal knowledge-base assistant using LLMs, agents, RAG, and LLMOps through six modules covering data pipelines to deployment.

Your second brain needs more than a chatbot demo second-brain-ai-assistant-course is an open-source course repo from Decoding AI for builders who want to create a personal knowledge-base assistant with LLMs, agents, RAG, and LLMOps. It helps you move from scattered notes to an end-to-end assistant by walking through six modules: data pipelines, dataset generation, fine-tuning, deployment, advanced RAG, and agentic inference/observability. Key features: • Six-module path – covers architecture, ETL, fine-tuning, deployment, RAG, and LLMOps • Offline + online apps – separates ML/data pipelines from the assistant inference pipeline • Notion-friendly data flow – uses a Second Brain knowledge base, with a public snapshot so a Notion account is optional • Real LLMOps tooling – includes ZenML, Opik, Comet, Unsloth, MongoDB, Hugging Face, and OpenAI • Builder-first setup – module docs, runnable code, uv/ruff, and Docker infrastructure included It’s open-source (MIT license). Link in the reply
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Your second brain needs more than a chatbot demo

second-brain-ai-assistant-course is an open-source course repo from Decoding AI for builders who want to create a personal knowledge-base assistant with LLMs, agents, RAG, and LLMOps.

It helps you move from scattered notes to an end-to-end assistant by walking through six modules: data pipelines, dataset generation, fine-tuning, deployment, advanced RAG, and agentic inference/observability.

Key features:

• Six-module path – covers architecture, ETL, fine-tuning, deployment, RAG, and LLMOps • Offline + online apps – separates ML/data pipelines from the assistant inference pipeline • Notion-friendly data flow – uses a Second Brain knowledge base, with a public snapshot so a Notion account is optional • Real LLMOps tooling – includes ZenML, Opik, Comet, Unsloth, MongoDB, Hugging Face, and OpenAI • Builder-first setup – module docs, runnable code, uv/ruff, and Docker infrastructure included

It’s open-source (MIT license).

Link in the reply

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