Practice End-to-End Data Science Workflow - 17.2 | 17. Case Studies and Real-World Projects | Data Science Advance
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End-to-End Data Science Workflow

17.2 - End-to-End Data Science Workflow

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Learning

Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is the first step in the data science workflow?

💡 Hint: It's about understanding what you need to solve.

Question 2 Easy

Name a common method for data collection.

💡 Hint: Think about how companies gather feedback.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is the main goal of the data cleaning process?

To organize data
To improve data quality
To visualize data

💡 Hint: Think about what happens with bad data.

Question 2

True or False: Feature engineering is unnecessary if you have a good dataset.

True
False

💡 Hint: Consider if just having a good dataset is enough.

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Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

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.

💡 Hint: Use the workflow steps as guide posts.

Challenge 2 Hard

Discuss the impact of poor problem definition on a data science project. Provide examples of its effects.

💡 Hint: Think about the implications of not addressing specific goals.

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