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Personalized learning paths for learners with different backgrounds #6

@ShengxuanQUAN

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@ShengxuanQUAN

The current general learning guide provides a helpful instruction, but learners may come from different academic backgrounds and may need different types of entry support.

For example:
· Biology-oriented learners may need more support with image arrays, cv concepts and computational workflows.
· CS-oriented learners may already know basic info and skip some of the chapters and delve straight into bioimage entext etc.
· Cryo-EM-oriented learners may understand the domain problem, but may need more support with ML-related tools...

So a possible improvement I think would be to keep the current general learning guide, but add optional entry paths or short notes for different learners. And this could help learners decide which parts to review carefully and which may be able to skip.

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