Practice Best Practices For Real-world Data Science Projects (17.9) - Case Studies and Real-World Projects

Practice: Best Practices for Real-World Data Science Projects

Lesson 17.9Case Studies and Real-World Projects

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8 questions

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2 cards from this section. Quick, good the night before a test.
Exercise
6 questions · about 4 min · pass mark 70%. Hints available.
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Quiz
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6 sample questions

Question 1.
What is the primary purpose of understanding the business context in a data science project?
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Think about how projects aim to solve real-world issues.
Question 2.
How can version control benefit a data science project?
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Consider how you share work with a team.
3Question 3.
Why is understanding the business context important in data science?
- It helps in choosing the right programming language
- It ensures alignment with business goals.
- It makes documentation unnecessary
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Consider what guides the direction of a project.
4Question 4.
True or False: Documentation is optional in data science projects.
- True
- False
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Think about how others may later use your work.
Question 5.
Propose a strategy to implement GDPR compliance in a new data science project involving user data.
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Consider all stages of the project lifecycle.
Question 6.
Analyze a case where inadequate documentation hindered a data science project. What could have been done differently?
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Think about communication breakdown and lost knowledge in teams.

4 more questions in this section. Enroll free to practise them all.