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学生对 Johns Hopkins University 提供的 Building a Data Science Team 的评价和反馈

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3,324 个评分

课程概述

Data science is a team sport. As a data science executive it is your job to recruit, organize, and manage the team to success. In this one-week course, we will cover how you can find the right people to fill out your data science team, how to organize them to give them the best chance to feel empowered and successful, and how to manage your team as it grows. This is a focused course designed to rapidly get you up to speed on the process of building and managing a data science team. Our goal was to make this as convenient as possible for you without sacrificing any essential content. We've left the technical information aside so that you can focus on managing your team and moving it forward. After completing this course you will know. 1. The different roles in the data science team including data scientist and data engineer 2. How the data science team relates to other teams in an organization 3. What are the expected qualifications of different data science team members 4. Relevant questions for interviewing data scientists 5. How to manage the onboarding process for the team 6. How to guide data science teams to success 7. How to encourage and empower data science teams Commitment: 1 week of study, 4-6 hours Course cover image by JaredZammit. Creative Commons BY-SA. https://flic.kr/p/5vuWZz...
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Applicable teachings

（79 条评论）

Brief, helpful lectures

（11 条评论）

热门审阅

PV

Jan 22, 2017

Good overview of forming Data science team. The challenges are typical of any SDLC project. However I was looking to glean some specific challenges between DSc team and product or marketing teams.

JA

Apr 15, 2018

Excellent content - delivery could be improved somewhat but happy overall. Lots of practical advice relevant to the job and team dynamics. Read the supplementary material/links

筛选依据：

126 - Building a Data Science Team 的 150 个评论（共 449 个）

创建者 Manuel E

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Jul 3, 2019

Excellent course. Liked the practical approach to interviewing.

创建者 RAJANIPOTTURI

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Sep 29, 2018

Very good course. Narrated team building process in easy steps.

创建者 黄俊皓

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Nov 30, 2017

the course is easy to learn , thank all that the course teacher

创建者 Jesus P

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Jul 26, 2017

very useful information with excelent and enjoyable exposition

创建者 Jociana L

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Sep 1, 2020

Nice Content! Pratical and easy to follow. Loved this module.

创建者 Edij

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Dec 30, 2017

Excellent introduction to how to build a data scientist team.

创建者 Pascal U E

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Oct 29, 2018

Good course for Data Scientist manager, I fully recommend it

创建者 Michael F

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Jan 18, 2018

nice, easy to follow introduction and guidlines to the topic

创建者 Abdul W

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Nov 19, 2017

Thank you very much Instructors for introducing this course.

创建者 Mohammad Z R

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Aug 20, 2017

Concise & good overview on Data team building & management.

创建者 Dejan K

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Aug 14, 2020

first time took a course on coursera. enjoyed quite a bit.

创建者 Gustavo V

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Mar 30, 2019

Usefull information to start building a data science team.

创建者 Som D M

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Feb 21, 2017

A quick and Great introduction on building effective Teams

创建者 Luis E C

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Jan 7, 2016

Excellent resource for a manager in data science projects.

创建者 Paulo B S

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Jul 4, 2019

Excelent combination between management and data science.

创建者 Nisha S

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Aug 26, 2017

This course is a good-start for new Data science managers

创建者 Sateesh K R

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Mar 9, 2016

Excellent Course for everyone keen to learn data science.

创建者 R. K R

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Jun 13, 2025

it was very useful for Beginner of Data Science Students

创建者 Piyapong B

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Dec 5, 2016

Very informative course on building a data science team!

创建者 Ashish L

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Apr 20, 2019

Very nice overview of how to build a Data Science Team.

创建者 Lewis Z

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Sep 18, 2020

Really great lectures and would recommend this course!

创建者 Ashish P

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Jul 1, 2020

Great Understanding of how to build data science team

创建者 Lech H

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Apr 15, 2021

Very practical hints based on the actual experience.

创建者 Livia d

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Mar 6, 2019

Straight to the point! Very objective information.

创建者 Claudia K J

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Feb 5, 2019

EXCELENT CURSE, SO WELL EXPLAINED AND WELL PLANNED