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Learner Reviews & Feedback for Building a Data Science Team by Johns Hopkins University

4.5
stars
3,156 ratings
436 reviews

About the Course

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...
Highlights
Applicable teachings
(79 Reviews)
Brief, helpful lectures
(11 Reviews)

Top reviews

NN
Dec 14, 2017

This course was an exceptional experience where it introduces me to building a data science team, its challenges, nuances and also what kind of approach to take while building and sustaining the team.

SM
Jan 14, 2021

Very well organized. Might consider adding couple of additional speakers with with more executive and management level experience with organizations that successfully implemented Data Science.

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351 - 375 of 429 Reviews for Building a Data Science Team

By Muhammad A S

May 15, 2020

Simple, and full of examples.

By Richard B

Jul 19, 2017

really good practical content

By Onur G

Apr 2, 2018

It covers all the essentials

By Clovis J

Nov 22, 2020

Very informative course

By Supriya M

Mar 12, 2018

Excellent Introduction.

By Atila T

Sep 26, 2017

Clear. Compact. Good.

By Christopher L

Apr 25, 2018

Good introduction.

By Elimane N

Apr 20, 2019

Very nice course

By Francos G S A

Jan 17, 2021

nice quizzes...

By Ivan T

Apr 19, 2020

Good overview.

By Pranjal S

May 28, 2020

Great Course

By Marianne O

Feb 23, 2018

Very helpful

By SATISH R

Jun 1, 2017

great course

By Asad M

Mar 18, 2020

good course

By Sourav P

Feb 26, 2018

Good course

By GORANTLA S K ( 2 B

Jul 7, 2020

Bit tough

By Ramkumar

Jun 27, 2017

Great one

By Paulose B

Oct 19, 2016

too pricy

By VERONICA C

Sep 16, 2017

Great ad

By Augustina R

Dec 25, 2016

If you know anything about management, specifically software engineering management, this course won't tell you anything new. It's very high level survey of best practices. I'm currently working as a software engineer on data science problems alone on my team. I wanted some idea of how data science teams are typically structured for when I need to talk about my work to my chain of command and my peers and for interacting with other dedicated data science teams at my company. I feel I got a pretty good idea of that and a better understanding the roles in an ideal team. I also feel prepared for the future if I were to apply for a role on a dedicated data science team. As far as actually building a team myself, I think this course won't really give you that if you don't already have other management experience, but it does give you some insight on the specifics of data science people. Finally, Quizzes could use some review, the answers don't often line up grammatically with the questions. Also the one with the instructor's LinkedIn profile linked doesn't work because LinkedIn covers the content and wants you to create an account. A link to a resume or something might be better.

By Mauricio M M

Jun 30, 2017

I know the course was about Building a data science team but it talked a lot about interactions. I missed a little bit a deeper exploration about those interections. I mean, how marketing or business teams demand data science projects to the data science team? How deep do they have to brief? Also, specially to the data science executive, how to distinct requests that are really for data science experiments and those that are not (and can be executed by "simple" business intelligence analyses)?

By Sheila O

Dec 27, 2020

Overall the course was informative, but as an experienced manager, I would like more specific coverage of managing data work and less coverage of general management/motivational principles. There was a very small but important section on how to address peer review and input on work product - expanding that section to cover other data science/engineering specific practical challenges would provide more value. You could completely eliminate the "onboarding" section, as that is really basic.

By Paul C

Nov 15, 2016

For most people this might be four stars. There is solid content here, but I couldn't help but feel a lot of this stuff is fairly standard OD/management material and in some ways, it felt like asking, say, a project manager to deliver a data science course. If you have never done any managerial training or read material on intrinsic motivation, org and team culture, then you will get value. For me this was pretty stock

By Dan K

Mar 29, 2017

Good overview for those without management experience. For experienced folks -- probably a good number since this is an Executive Data Science course -- it was pretty basic. Also some of the elements come down to management style. For some, other approaches have worked well and might not be ready to switch philosophies based on the course.

Otherwise, pretty good.

By Karun T

Jan 17, 2017

Content was good and questions were well-thought. Video lectures however would need written notes to accompany them. Also when videos are as long and fast-paced as it is in the course it would be nice to throw the major point in discussion on the background,this would help clarify and focus the idea the lecturer is trying to convey.