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.
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.
автор: Mauricio M M•
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)?
автор: Sheila O•
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.
автор: Paul C•
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
автор: Dan K•
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.
автор: Karun T•
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.
автор: Gonzalo G A•
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.
автор: Naim J•
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.
автор: Neil K•
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!
автор: Chip J•
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.
автор: Christopher P•
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.
автор: Vijay S K•
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.
автор: Niels v G•
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
автор: Marc P•
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.
автор: Katherine d T•
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.
автор: Bart v d G•
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
автор: YIMIN Q•
This class might not be designed for people who have had years of managerial experiences in a large organization.
автор: Jose C O B•
The information is useful, but I think the five courses in the specialization could be merged into a single one.
автор: Paul D•
Informative but many of the insights apply to good managers in general; not just for data science teams
автор: Daniel D•
As having experience managing researcher the subject is not completely new, so it can seems long.
автор: pamandeep s g•
Good interesting material but the quizzes were badly designed and did not test concepts well.
автор: Peter L•
Added value is highly dependent of your experience with data analysis or data engeneering
автор: Grant C•
There could be more work in the assignments in this course. The Quizzes are very simple.
автор: Shafeeq I•
Good on understanding roles each has to play. but very lengthy to explain those.
автор: Chen S•
Great idea and syllabus.
The videos are too short and missing some explanations.