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collaboration/learning_goals.md

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# Learning Goals
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## Collective
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As Team GreenFrontier, our shared goals for these exercises are:
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**Our shared goals for these exercises are**:
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Strengthen our collaboration and communication skills in a technical context by
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working through coding challenges together and exchanging ideas openly.
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Develop a consistent and professional workflow for writing, structuring, reviewing,
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and improving code using shared standards and GitHub best practices.
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Write clear, readable, and well-documented solutions, including modular functions,
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meaningful commit messages, polished notebooks, and accessible READMEs.
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Support each other’s learning through constructive feedback, code reviews,
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and active knowledge sharing—so everyone learns from everyone.
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Build confidence and creativity in how we approach problems as a team, experimenting
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with new techniques and tackling challenges with curiosity.
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Deepen our data-science foundations through weekly practice with EDA, visualization,
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and fundamental statistics applied to real datasets.
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Create an inclusive, supportive learning environment where all voices are welcomed,
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questions are encouraged, and leadership is shared.
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Communicate insights clearly by translating technical results into simple explanations,
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one-pagers, and concise presentations.
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Promote reproducible, future-friendly work through automation, versioning,
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structured pipelines, and documentation that helps future collaborators.
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## Individual Learning goal (Kervens)
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Build consistency and personal discipline by dedicating regular time to research,
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review, and independent practice.
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Apply personal agency tools to set clear intentions, monitor progress,
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and stay accountable throughout the project.
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Strengthen collaborative coding skills by mastering GitHub workflows
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(branching, pull requests, conflict resolution) and writing meaningful commit messages.
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Develop clear technical communication by maintaining well-commented scripts,
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structured notebooks, and visual explanations of decisions.
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- Strengthen our collaboration and communication skills in a technical context.
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- Develop a consistent workflow for writing, reviewing, and improving code.
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- Practice writing clear, readable, and well-documented solutions.
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- Support each other’s learning through feedback and knowledge sharing.
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- Build confidence in tackling coding problems as a team.
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Create reproducible workflows for data loading, cleaning, and modeling through
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modularized code and versioned notebooks.
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## Individual
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<!--every member can write his own name and then
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his learning goals and objectives anytime --!>
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Apply data science to real-world questions—especially related to education, policy,
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or social outcomes—and document insights for both technical and non-technical audiences.

collaboration/petit.c

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