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Managing Data Science

You're reading from   Managing Data Science Effective strategies to manage data science projects and build a sustainable team

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Product type Paperback
Published in Nov 2019
Publisher Packt
ISBN-13 9781838826321
Length 290 pages
Edition 1st Edition
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Author (1):
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Kirill Dubovikov Kirill Dubovikov
Author Profile Icon Kirill Dubovikov
Kirill Dubovikov
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Table of Contents (18) Chapters Close

1. Section 1: What is Data Science? FREE CHAPTER
2. What You Can Do with Data Science 3. Testing Your Models 4. Understanding AI 5. Section 2: Building and Sustaining a Team
6. An Ideal Data Science Team 7. Conducting Data Science Interviews 8. Building Your Data Science Team 9. Section 3: Managing Various Data Science Projects
10. Managing Innovation 11. Managing Data Science Projects 12. Common Pitfalls of Data Science Projects 13. Creating Products and Improving Reusability 14. Section 4: Creating a Development Infrastructure
15. Implementing ModelOps 16. Building Your Technology Stack 17. Conclusion 18. Other Books You May Enjoy

Summary

Congratulations on finishing this book! I hope that it helped you deepen your knowledge of data science and systemize management techniques for data science projects. Please don't leave what you have read about the theory of data science behind. To master the concepts we have covered in this book, you should apply them to your daily work. I also strongly advise you to acquire a growth mindset, if you haven't already. You will be amazed by how far you can go by learning something new each day, even if it's the smallest bit of knowledge. No book can fully cover every aspect of data science management, but you can continue this journey by referring to one of the books mentioned in this chapter or discovering your own path while mastering data science.

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