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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

In this chapter, we explored the complex topic of building and sustaining a team. First, we dived into the concept of team balance and looked at why it is crucial for a team's survival in the long term. Then, we learned about several leadership styles, including the situational leadership model and leadership by example. We then saw how we can create good task descriptions using the SMART criteria. We also mentioned empathy and active listening as the most important soft skills of a leader. We also explored the concepts of continuous learning and a growth mindset. Finally, we saw how a performance review process can help learning habits develop in your team.

This chapter concludes the Building and Sustaining a Team section of this book; congratulations on finishing it! The next section of this book will cover the topic of managing data science projects.

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