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4 cards from this section. Quick, good the night before a test.
What are the key components that should be included in a data science portfolio?
Think about what would demonstrate your skills effectively.
Why is documentation important in a project?
Consider the role of communication in data science.
What is the minimum number of projects to include in a data science portfolio?
Think about quality versus quantity.
True or False: Dashboards are mandatory components of a data science portfolio.
Recall the flexibility in building portfolios.
You have completed a project predicting customer churn. Outline a presentation plan for your portfolio that includes project documentation, code sharing, and EDA.
Consider the flow of information that caters to both a technical and non-technical audience.
Devise a strategy for enriching a data science portfolio beyond project examples. Discuss at least three strategies.
Think about engaging with the data science community and continuing learning.
5 more questions in this section. Enroll free to practise them all.
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