Introduction
Theory is good, but practice can be better
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What you should know
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1. Data Stories
Why perfect predictions can backfire
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Why inaccurate modelling can cause harm
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Why causality needs careful thought
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Why experiments need ethical considerations
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How dashboards and visualizations can clarify or obscure
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Why early modeling success should not be taken for granted
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Why effective communication between stakeholders matters
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Why survey quality shouldn't be taken for granted
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Conclusion
Boost your data skills
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