2.1 - What to Include
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Practice Questions
Test your understanding with targeted questions
What are the key components that should be included in a data science portfolio?
💡 Hint: Think about what would demonstrate your skills effectively.
Why is documentation important in a project?
💡 Hint: Consider the role of communication in data science.
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Interactive Quizzes
Quick quizzes to reinforce your learning
What is the minimum number of projects to include in a data science portfolio?
💡 Hint: Think about quality versus quantity.
True or False: Dashboards are mandatory components of a data science portfolio.
💡 Hint: Recall the flexibility in building portfolios.
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Challenge Problems
Push your limits with advanced challenges
You have completed a project predicting customer churn. Outline a presentation plan for your portfolio that includes project documentation, code sharing, and EDA.
💡 Hint: 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.
💡 Hint: Think about engaging with the data science community and continuing learning.
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