14 дек. 2017 г.
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.
14 янв. 2021 г.
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.
31 мар. 2019 г.
Well thought and constructed instructional materials. Easy to understand and more practical. I actually struggled with the quizzes unlike the First Course in this executive program.
автор: Rafael H•
15 апр. 2019 г.
Horrible experience with one quiz where I lost hours just because it is completely misleading, tricky and bad formulated. Many people had the same experience from long time ago and they didn’t have the courtesy to fixed it.
автор: Sachin G•
29 июня 2017 г.
was more generic rather than data science specific.
автор: Sohail B•
7 сент. 2017 г.
Brief Profile: Sohail Butt
I am a man of 58 years old and having an experience of almost 30 years of Business Management of Pharmaceutical & Nutraceutical Industries of Pakistan. Presently I am having my own Consulting Company " AIMMS CONSULTING" and extending my services as Management Consultant to different companies of said sectors.
I am of the conviction that learning is never ending and have a habit of learning new ideas about my favorite subject about Data Science. Although I have the limited usage of this subject in my working areas but I love to know about new areas of different specialties.
I really appreciate highly the efforts of respected instructor and enjoyed the course material and videos presentation of this course. Mind blowing approach was adopted especially in the basic components of Building A Data Science Team Data Analysis.
MY PERSONAL HUMBLE REQUEST, Please make also the important components of course material as a part of this Certificate with % AGGREGATE so that it has a much more worth & impact for the courses participated.
A separate Transcript must be issued with having Aggregate % Score and important Components of participated course.
Thanks & best wishes to all Coursera Team.
автор: Anand S•
30 апр. 2017 г.
This class was a great introduction to the topic of building a data science team.
The material was practically oriented, cited a lot of relevant external sources (e.g., news articles about data science), and was easy to understand.
The production quality was excellent - easy to listen to, ready to follow the slides, and the questions immediately followed each short segment.
I would have preferred it if the Professor had gone through different examples of data scientist and data engineering resumes to show me what performers in each quintile look like and what signals distinguish members of each quintile from the higher or lower quintile. Apart from the signals, and interview questions used to elicit these signals, how would the ability levels be different.
автор: bojana m•
8 июня 2016 г.
Well organized body of knowledge on how to build efficient data science team, from 0 to 60. Addresses a number of challenges including how to build an inter-disciplinary team, what to expect from practitioners from different disciplines, how to recognize right candidates, how to assign the right mix of practitioners to right business problems, how to cross-polinate the knowledge, how to keep feedback loops at professional level as it's fraught with potential for conflicting opinions, when to stop analysis, how to empower the team to initiate next iterations with business, common pitfalls and more. Worth every $ and all the time you'll spend on it.
автор: Shibaji M•
20 сент. 2015 г.
This is a great course for helping you decide where you fit in the data science domain. The content is very clear, informative and have definite suggestions and conclusions. Unlike most of the information available on this topic, which mostly says that you need to be a unicorn to be in this space, this course talks sense, divides scope, suggests achievable targets and you can plan and assess rationally.
Also Jeff is a classic teacher,it's always rewarding to listen to him whatever be the topic.
27 июня 2020 г.
It explains very simple the things you will require if your are planning to create a team of data analytics.Like understaing the roles of analyst, engineer and manager, consider important factors as empowerment and control expectations of what data anlysis can achieve.
Just consider increasing the time for reading sessions, they usually take more than the 10min said, and having the more realistic time, help us to plann our study sessions.
автор: tommy c•
23 мая 2016 г.
great for existence human and android based life-form simulation internal lifestyle...
The course improves life within the simulation 10 fold at least(when combined with the other specialization courses) ...
Perfect learning tool for those who have worked professionally in research field sin our simulation and yet now have a touch of "the turrings" or you know : CBI...
Special thanks to the designers of the course.
Top scores for coursera.org &John Hopkins ...
автор: José A R N•
30 сент. 2016 г.
My name is Jose Antonio from Brazil. I am looking for a new Data Scientist career.
Please, take a look at my LinkedIn profile: https://www.linkedin.com/in/joseantonio11
I did this course to get new knowledge about Big Data and better understand the technology and your practical applications.
The course was excellent and the classes well taught by teachers.
Congratulations to Coursera team and Instructors.
автор: Mark H•
24 авг. 2017 г.
Very informative and easy to digest. I am the Manager of a Data Science team Manager, so I'm a bit removed from the team and this course is helping me appreciate and understand more about what goes on within the team and how we as an organisation can get more from them and they from the organisation. Very good lectures, with transcripts and all well paced in small, easy to swallow chunks. Very good.
автор: Allen J M A•
27 авг. 2017 г.
I really like the way this course was divided into manageable sections. It is really engaging and fun (and for those of you wondering, no, it's not boring at all). The course offers all the basics of how to build a data science team. I look forward to more courses like this from JHU and I would love to complete more courses and specialization courses from JHU. Kudos and Thank you!
автор: William J W•
20 июня 2018 г.
What a great overview of a data science team and what it takes to build one. As a graduate with a MBA, concentration in DSBA, it took this course to really understand the makeup of a data science team and how to build one. I plan on meshing my understanding of how a business works with my newfound understanding of DS teams!
автор: Abhishek V K•
21 июля 2019 г.
This is an excellent course for those who want to conceptualize a Data Science role or team for their organizations. The course not only explains the roles played by a data scientist, data engineer and data science manager, but also cover the intricacies working with the data science team. Their interaction with othe
автор: James L•
27 мар. 2017 г.
As usual the team does a great job of distilling complex ideas without sacrificing the quality of information. Data Science is a complicated field. Don't be fooled by the topics, the walk before you run approach is super productive for your learning curve if you're not native to this field.
автор: Bose M•
11 дек. 2020 г.
Its an exceptional course. A must pursue course for every manager either as new learning or refresher of knowledge.
A great thanks to course trainers. Their teaching approach is very target oriented to put the concepts in student brain in simpler and efficient way.
автор: ARVIND K S•
29 мая 2020 г.
Very useful course for data managers on how to build, empower, support teams and communicate with them.. Not the usual statistics or quants, but real life scenarios at work places beautifully brought out by someone who must have experienced them.
автор: Jill M W•
19 июня 2017 г.
I really enjoyed learn the specific roles of each person in a data science team. By learning the role of each team member, it is a start in learning how to manage each individual role and the whole class came together in a cohesive way.
автор: Anna S•
24 нояб. 2017 г.
Very interesting, because it deals with "soft skills" too and handling these seems increasingly important. It helps you understand how a data team works and how to interact with them and manage the environment best. I find this course very useful.
автор: Jorge Q G•
23 мар. 2020 г.
Everything is new to me so I found it very interesting. Profesor might understand that he has all kind of backgrounds in the audience and maybe for some of us English is not our native language so, please slow down when speaking. Thanks so much!
автор: Noah H•
14 мар. 2020 г.
I thought it was a very informative and helpful course! As a newcomer to the subject, the course provided me with a very useful framework for continued learning and understanding of the data science topics applied in organizational settings.
автор: Ramy M•
4 окт. 2015 г.
Thanks for your efforts, I can't put my hand on something specifically and say good job! but you did a great job! thanks for sharing your knowledge for everyone on earth without any complication!
You have taught me a lot and I own you a lot!
автор: Marc-Eric L•
23 дек. 2019 г.
Very nicely done. I like that it focused on truly making data scientists performant in the real world of organizations. In scientific work, we tend to underestimate the impact of psychology and social sensibilization to get to results.
автор: Victor O•
5 мая 2020 г.
By far, one of the most important courses for managers beginning in data science. They go straight to the point of recruiting the right people for the right roles, managing the team and dealing with common problems. Really useful!
автор: Ashley K•
27 дек. 2017 г.
Great overview, especially if you're a first time manager or getting ready to lead your first data science team. Formative, but just listening (took me one afternoon), gives me more confidence moving forward.