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

4.5
stars
3,199 ratings
439 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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276 - 300 of 433 Reviews for Building a Data Science Team

By Don R

Mar 9, 2021

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

Dec 20, 2015

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,

Giacomo

By John H

Sep 29, 2015

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

Sep 17, 2017

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

Feb 22, 2017

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

Apr 3, 2016

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

Dec 1, 2017

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

Oct 10, 2016

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

Nov 3, 2020

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

Jul 25, 2020

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

Jun 30, 2017

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.

Best,

Miomir

By Pascal N

Nov 18, 2015

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

Aug 4, 2020

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

Aug 11, 2017

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

Jun 15, 2019

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

Feb 20, 2018

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

Jan 23, 2017

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

Dec 4, 2020

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

May 22, 2016

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

Nov 21, 2017

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

Apr 16, 2018

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

Jan 31, 2017

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

Apr 4, 2018

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

Mar 14, 2016

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

Aug 15, 2017

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.