Bit tough

Great one

too pricy

Great ad

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.

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)?

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.

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

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.

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.

Some of the videos are very basic concepts on how to lead a team (i.e.: Management strategies, common difficulties,...). It is already known things for a manager with some experience leading teams. This course could be shorter.

although important. The content is a bit primitive for professionals who have been in the corporate world for more than a decade. It only confirms that team work is essential in any discipline and any practice.

While a good introduction for those new to personnel management and leadership roles, this was pretty basic for someone like myself. Great lecturer, great points made, most all of them familiar to me. Thanks!

Some good content. Main reason for not scoring hire is there seemed to be too much overlap with standard management practices not unique to data science teams, such as the on-boarding section.

The teacher spoke too fast.The content does not summarize the main idea, it is difficult for learners to grasp the content.The teacher should summarize the main points of the presentation.

This was a fine overview however I was hoping to drill down into more detail on some of the roles and responsibilites data teams can have. For example data architects, stewards etc.

A lot of content is more or less generic, same as any software engineering team building. Specific scenarios should have been covered to make it data science team specific.

Building a Data Science Team does indeed contain helpful recommendations for starting data science teammanagers/executives; for me it had a little too much of a Hu

This course is mainly theoric.

The practice depends on opportunity to apply it on your work place.

Directly, this course doesn't provide any new verifiable skill.

It was a bit.... general. That could be a bias of mine, as I have done quite a bit of management-type work, so maybe it didn't feel that new or informative.

Some helpful suggestions but too much content on general, common sense management principles. Should be more focused on specifics of data science.

A lot of open doors if you have management experience but provides some overview of what to take into account specifically for a data science team

This class might not be designed for people who have had years of managerial experiences in a large organization.

The information is useful, but I think the five courses in the specialization could be merged into a single one.

Informative but many of the insights apply to good managers in general; not just for data science teams