I want to learn Qiskit in a structured and reliable way with the long-term goal of becoming an open-source contributor to the Qiskit ecosystem. However, I am struggling to find a clear and efficient learning roadmap focused on Qiskit development, not just high-level quantum computing concepts.
Currently, I see three major learning approaches, and I have tried all of them, but each has limitations:
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Directly reading Qiskit documentation
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The documentation is comprehensive but very extensive.
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As a beginner/intermediate learner, it is difficult to identify what to read first, what can be skipped initially, and what is essential for development and contribution.
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Progress feels very slow and unstructured.
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Learning from AI tools (e.g., ChatGPT, Gemini)
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These tools are helpful for clarification and examples.
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However, they are not fully reliable as a primary learning source, especially for internal Qiskit design, best practices, and up-to-date development workflows.
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QISKIT Video courses on YouTube (e.g., Qiskit Global Summer School)
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These courses are excellent but mostly focus on high-level concepts and applications.
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They do not cover Qiskit internals, codebase structure, contribution workflow, testing, or how to transition from “user” to “developer.”
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What I am looking for:
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A robust, step-by-step roadmap specifically for learning Qiskit development
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Guidance on:
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Which parts of the Qiskit documentation are must-read for contributors
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How to move from using Qiskit to understanding its internals
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Recommended order of learning (Terra, Aer, primitives, transpiler, etc.)
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How to start contributing (issues, tests, documentation, code)
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Advice from experienced contributors on what actually worked for them
If you are an active or past Qiskit contributor, or if you followed a successful path to contributing, your guidance would be extremely valuable.
Thank you in advance for your help.