Practice End-to-end Data Science Workflow (17.2) - Case Studies and Real-World Projects

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8 questions

Flashcard drill
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
2 questions · about 1 min · pass mark 70%. Hints available.
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6 sample questions

Question 1.
What is the first step in the data science workflow?
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It's about understanding what you need to solve.
Question 2.
Name a common method for data collection.
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Think about how companies gather feedback.
3Question 3.
What is the main goal of the data cleaning process?
- To organize data
- To improve data quality
- To visualize data
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Think about what happens with bad data.
4Question 4.
True or False: Feature engineering is unnecessary if you have a good dataset.
- True
- False
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Consider if just having a good dataset is enough.
Question 5.
Create a plan for a data science project focusing on predicting sales. List each step of the workflow and provide a brief explanation for each.
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Use the workflow steps as guide posts.
Question 6.
Discuss the impact of poor problem definition on a data science project. Provide examples of its effects.
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Think about the implications of not addressing specific goals.

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