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.
By Don R•
I've taken the first two courses in this area. I've noticed a data science issue that seems to be 'skirted around'....that is understanding the actual data and how it is created. I work in a health care organization. Our Epidemiologists are 'quasi-data scientists' however, their main strength is data analysis and presentation. We have one research database that is well documented and uses world wide standards....this doesn't cause any challenges. However, our clinical system is a transactional database that is used for managing patient appointments, treatments, and their electronic chart. There are two challenges....first, the epidemiologists have very little understanding of the process and business rules that are used for entering data and they have a reluctance to dig out that information. This is a big issue for them because when they approach data engineers to provide them with data they don't understand the 'business' issues associated with that data and therefore there requests are often not meaningful. An intermediary of some sort is needed to help the epidemiologists understand what they are asking for and what problems they will encounter with the data. The second, somewhat lesser problem is that the the clinical management system database is in no way optomized for data extraction. It's a transactional database with hundreds of tables and therefore is not directly usable by an epidemiologist. We have dedicated data engineers who extract data from this database. I think there is a gap in our organization between the Epidemiologists who are statisticians and the data engineers ...... this gap is my concern.
By GIacomo V•
I really enjoyed this course and I have found a lot of similarities with issues and challenges that I face every day at work. This has been very useful to me bot as a way to get inspired on new ideas and techniques, and as a way to confirm what I am already doing.
However, there were few occasions where I found the quizzes not to be clear enough.
In some instances this was due to the fact that the question asked required some extra knowledge that couldn't possibly be achieved only by reading the course material or listening to the class. I was lucky I new the answers because of my personal experience but it seemed quite unfair in my opinion. Also lectures materials are very short and don;t provide any extra information.
In other cases, the answers, especially when there were multiple answers didn't seem to be clear enough and sometimes contradicting what I had listened in the class. I don't remember specific cases at the moment, however I have left feedbacks throughout the course. You should have my feedbacks where I mentioned specific questions that in my opinion were confusing.
Hope this helps,
By John H•
Good coverage in a very fast intro to the subject. Definitely take away some things I am able to put into use in my work. I get the feeling this is quite a new course (compared with the very well established Data Science Specialization) and does not have the student interaction base yet. I hope this aspect develops - perhaps even with the TAs. For this level course student interaction could be even more valuable than the more hands on data science subjects. Hope this specialization takes off as well as the DSS did!
By Stellios S•
Good course that puts various aspects of a Data Science manager day-to-day activities into perspective presented by a talented instructor. However, I feel that there are a couple of things that could fit into the course like the role of Data Curators in a team or the distinction between Analysts and Scientists (which, I know, is not always clear). The notions of KPIs and OKRs could also have been pointed out when it comes to setting goals and managing.
By Cyril B•
A very interesting course focus on the true life with data science teams. This course is more about the day to day life and problem to manage a data science team and less about pure organization. The financial aspects are not covered by Jeff nor the complex problems of people organization. I have noticed that I was the sole person to post on the forum.
By Reinaldo B N•
I have studied this course as part of the Executive Data Science Specialization. I think this set of four courses meet my objectives by providing a very nice overview on the key points of data science projects. They are good to give a flavor on data science and data science projects helping decide if you want to search for more in depth knowledge.
By Rong-Rong C•
Informative overview of the various roles in a data science team. The course is well-paced with plenty of supplemental curriculum to add substance beyond hiring. This covers the qualitative qualities that define and differentiate the human interactions of a successful team from that of the technical.
By Ben W•
A good, enjoyable course with some interesting additional reading. I think I would have preferred a little more detail/content to have given it a full five stars. That said...I am very happy to have taken and passed the course. Thank you all involved. Now on to 'Managing Data Analysis'!!
By Charissa B•
Really helpful for a manager of a data science team. Not overly technical for those without a data science background. Would certainly recommend to those in management positions who need to get up to speed on data science and managing teams involved with this discipline.
By VIDHYAMBIKA S•
A Very useful course and is recommended for leaders, entrepreneurs who plan to organise and manage a data science team in their company also recommended to all students who plan to become a data science manager or want to just know what makes a datascience team
By Miomir Z•
Data science part was very valuable to me while some basics of people management are just basic. Overall solid course that i would recommend. More advance/modern/popular tools such as coaching and shared leadership were missing to make it 5 stars.
By Pascal N•
Ver good with clear and on point material. I would suggest to include real life stories of success and failure some managers had in building a data science team, and discuss about the mistakes or the strengths of their recruitment process.
By Olga W•
Mostly relevant information and useful pointers for a quick introduction. Since I am already managing a data science team for over 2 years, I was looking for more in-depth insights and advice on solving a variety of problems.
By Matthias L•
It was a great overview of the different roles and also the interfaces between people and different teams. Nice to see that culture and communication were seriously discussed, showing awareness for organisational theory!
By Carlos A H•
Excellent insight and guidance on essential practices in building a data science team. Area of improvement is emphasizing python more than R as python has become the preferred programming language in data science.
By Julien N•
Nice explications of a data science team, its players and how they interact within their team and the other departments of their organisation.
The Capstone project is the perfect application of this class
By prasanna v•
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.
By Maxim S•
Quizes contain mistakes, some of them did not accept answers which are definitely right (as it was told ithe lectures). Some mistake were not improved since 2015, according to threads from forum.
By Ryan V•
Good but should come after the Managing Data Analysis for understanding better what the people you hire are actually going to do. Preventing the "Dilbertification" of the data science manager.
By Clifton d L•
I found this course useful, especially the hints regarding a code of conduct for Data teams and the interactions with other teams. Also a good refresher on general team-leadership/management.
By JOSEPH A•
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
By Vaughan W•
Good overview of the roles and skills needed, but loses a little momentum when it gets into the team management side of things, which is covered in many other business courses.
By Ravi K S•
1 start less because of the ever-confusing quiz questions. Hit and trials make you go mad, and insance when you figure out the correct answer that you couldn't have imagined.
By HYUN K•
This class had hard quiz.
Sometimes it seemed very basic, but some are hard unless you read and learn really well. Great class/knowledge. Practical real-life examples help.
By Jeffrey M S•
This course had a lot of practical, helpful guidelines for managing technology professionals in general, in addition to specific pointers for managing a data science team.