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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

An Ideal Data Science Team

Since you are reading this book, it's likely you already understand the importance of teamwork. You can complete a complex project with a team more efficiently than in isolation. Of course, one person can build a house alone, but by working with others, they will finish the house faster, and the result will be better.

When you work with a team, everyone can specialize in performing several closely-related types of work. To explore different specialties, let's look at an example of how houses are built. Building a roof requires one set of skills, while setting up electricity is completely different. As a manager, you need to have a basic understanding of all specialties, so as to understand all components necessary for completing a task. In the What is Data Science? section, you were introduced to the central concepts of data science. Then,...

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