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Opiniones y comentarios de aprendices correspondientes a Building a Data Science Team por parte de Universidad Johns Hopkins

4.5
2,454 calificaciones
335 revisiones

Acerca del Curso

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...
Aspectos destacados
Applicable teachings
(79 revisiones)
Brief, helpful lectures
(11 revisiones)

Principales revisiones

NN

Dec 15, 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.

JS

Mar 12, 2017

Extremely practical and essentially human, this was really interesting to better understand the different roles and how to help data science teams to work together, highly recommended

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151 - 175 de 328 revisiones para Building a Data Science Team

por humbert.sch@gmail.com

May 01, 2017

Excellent!

por Sohail B

Sep 07, 2017

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.

SUGGESTION:

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.

por Evangelos T

Aug 27, 2017

Great insight into how to build a data science team beyond common management issues that typically apply to team management.

por Danny D

Jan 29, 2017

Great course, learned lots about building and leading a data science team; and also some tips on keeping teams motivated and ensuing communication and collaboration works well.

por Zeev G

Mar 13, 2017

very good course for beginners, in my case I built the same team and processes by heart and it matched the suggestions in this course

por Shivakumar H

Oct 27, 2017

very informative

por Mahesh A

Aug 12, 2017

An excellent course. The different roles in a data science team and the challenges faced are well explained.

por James L

Mar 27, 2017

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.

por Sophie L B

Mar 04, 2018

very nice. The boundaries of skills between data engineers and data scientists are sometimes a little artificial but I enjoyed the material a lot.

por Matthew B

Apr 21, 2016

Great advice, helpful reference material.

por Craig O

Jun 19, 2017

Great overview of current approaches to management of data science/engineering professionals.

por Deleted A

Jul 30, 2016

Excellent overview of the structure and dynamics of data science teams in various types of organizations.

por chandrasekharan

May 23, 2017

Excellent course!!.Really liked it

por Muhammed G

Nov 05, 2016

Hi everyone !

It is my honor to appreciate what I learnt from this course. I love it,the university,and the instructors. It is a step forward for my carrier.

por Simon B

May 16, 2017

A great integrated perspective.

por Ben T

Nov 18, 2016

Great useful course

por Kshitij G

Feb 28, 2016

Precise and relevant, and gets one into the groove ethically and practically , on the nuances of on-line learning and ettiquette.

por Chris S

May 07, 2016

Great course

por James J

Oct 23, 2016

Really great course, quick yet informative!

por Terry L J

Jun 20, 2017

Excellent material.

por olgakl77

Feb 15, 2017

Nice course. Thank you.

por Jason J

Feb 14, 2018

Great overview of team roles / responsibilities, how the team can "fit" into the organization, and how to handle engagement with non data community

por Damon R

Sep 26, 2016

Thanks

por Michael F

Jan 18, 2018

nice, easy to follow introduction and guidlines to the topic

por Alvaro S R

Jul 20, 2018

Very useful course given a very good overview of the tasks, profiles and skills you need to build and manage a data science team.