Data Science practice

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1. Practice Data Science overview by building one step of a small real project feature and checking the result.

code-writing
beginnerData Science overview

1. Start from the Data Science overview lesson example.

2. Use sample input, output and edge cases instead of placeholder text.

3. Run the example and compare output before polishing.

2. Practice Data Science setup by building one step of a small real project feature and checking the result.

code-fix
beginnerData Science setup

1. Start from the Data Science setup lesson example.

2. Use sample input, output and edge cases instead of placeholder text.

3. Run the example and compare output before polishing.

3. Practice Data Science syntax by building one step of a small real project feature and checking the result.

output
beginnerData Science syntax

1. Start from the Data Science syntax lesson example.

2. Use sample input, output and edge cases instead of placeholder text.

3. Run the example and compare output before polishing.

4. Practice Data Science examples by building one step of a small real project feature and checking the result.

fill-blank
beginnerData Science examples

1. Start from the Data Science examples lesson example.

2. Use sample input, output and edge cases instead of placeholder text.

3. Run the example and compare output before polishing.

5. Practice Data Science workflow by building one step of a small real project feature and checking the result.

true-false
beginnerData Science workflow

1. Start from the Data Science workflow lesson example.

2. Use sample input, output and edge cases instead of placeholder text.

3. Run the example and compare output before polishing.

6. Practice Data Science validation by building one step of a small real project feature and checking the result.

mini-project
beginnerData Science validation

1. Start from the Data Science validation lesson example.

2. Use sample input, output and edge cases instead of placeholder text.

3. Run the example and compare output before polishing.

7. Practice Data Science debugging by building one step of a small real project feature and checking the result.

mcq
beginnerData Science debugging

1. Start from the Data Science debugging lesson example.

2. Use sample input, output and edge cases instead of placeholder text.

3. Run the example and compare output before polishing.

8. Practice Data Science best practices by building one step of a small real project feature and checking the result.

code-writing
beginnerData Science best practices

1. Start from the Data Science best practices lesson example.

2. Use sample input, output and edge cases instead of placeholder text.

3. Run the example and compare output before polishing.

9. Practice Data Science overview by building one step of a small real project feature and checking the result.

code-fix
beginnerData Science overview

1. Start from the Data Science overview lesson example.

2. Use sample input, output and edge cases instead of placeholder text.

3. Run the example and compare output before polishing.

10. Practice Data Science setup by building one step of a small real project feature and checking the result.

output
beginnerData Science setup

1. Start from the Data Science setup lesson example.

2. Use sample input, output and edge cases instead of placeholder text.

3. Run the example and compare output before polishing.

11. Practice Data Science syntax by building one step of a small real project feature and checking the result.

fill-blank
intermediateData Science syntax

1. Start from the Data Science syntax lesson example.

2. Use sample input, output and edge cases instead of placeholder text.

3. Run the example and compare output before polishing.

12. Practice Data Science examples by building one step of a small real project feature and checking the result.

true-false
intermediateData Science examples

1. Start from the Data Science examples lesson example.

2. Use sample input, output and edge cases instead of placeholder text.

3. Run the example and compare output before polishing.

13. Practice Data Science workflow by building one step of a small real project feature and checking the result.

mini-project
intermediateData Science workflow

1. Start from the Data Science workflow lesson example.

2. Use sample input, output and edge cases instead of placeholder text.

3. Run the example and compare output before polishing.

14. Practice Data Science validation by building one step of a small real project feature and checking the result.

mcq
intermediateData Science validation

1. Start from the Data Science validation lesson example.

2. Use sample input, output and edge cases instead of placeholder text.

3. Run the example and compare output before polishing.

15. Practice Data Science debugging by building one step of a small real project feature and checking the result.

code-writing
intermediateData Science debugging

1. Start from the Data Science debugging lesson example.

2. Use sample input, output and edge cases instead of placeholder text.

3. Run the example and compare output before polishing.

16. Practice Data Science best practices by building one step of a small real project feature and checking the result.

code-fix
intermediateData Science best practices

1. Start from the Data Science best practices lesson example.

2. Use sample input, output and edge cases instead of placeholder text.

3. Run the example and compare output before polishing.

17. Practice Data Science overview by building one step of a small real project feature and checking the result.

output
intermediateData Science overview

1. Start from the Data Science overview lesson example.

2. Use sample input, output and edge cases instead of placeholder text.

3. Run the example and compare output before polishing.

18. Practice Data Science setup by building one step of a small real project feature and checking the result.

fill-blank
intermediateData Science setup

1. Start from the Data Science setup lesson example.

2. Use sample input, output and edge cases instead of placeholder text.

3. Run the example and compare output before polishing.