Join Barton Poulson for an in-depth discussion in this video Team, part of Introduction to Data Science.
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- [Voiceover] Data science is often practiced in teams.…It's a collaborative effort.…Consequently, what you need are several people…working on the project with complementary abilities.…Determine which skills are necessary for the project…and recruit people accordingly, or develop accordingly.…Let's go with a quick example.…Assume we have a hypothetical data scientist named Anthony,…and he's strong in data visualization.…He has good coding ability,…but he has limited analytics experience.…
And in fact, if we took the five characteristics…and we created a profile for Anthony…where he rated himself on a zero to ten…on each of these things, maybe it would like that.…And I've got a dotted line here at eight to say,…that's the level that you need…in order to do the project well.…Now he's past there on graphics, he's doing great,…but it's not everything that he needs…in order to do the project the way that it deserves.…Fortunately, there's another person.…Our other hypothetical person we'll call it Abby.…
She's got great business experience,…
- The demand for data science
- Roles and careers
- Ethical issues in data science
- Sourcing data
- Exploring data through graphs and statistics
- Programming with R, Python, and SQL
- Data science in math and statistics
- Data science and machine learning
- Communicating with data
Skill Level Beginner
R Statistics Essential Trainingwith Barton Poulson5h 59m Intermediate
1. What Is Data Science?
2. Fields of Study
Ethical issues2m 39s
4. Data Sources
5. Data Exploration
8. Applied Statistics
9. Machine Learning
Next steps2m 17s
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