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 course is part of the Executive Data Science Specialization
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Executive Data Science SpecializationJohns Hopkins UniversityAbout this Course
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Learner Career Outcomes
35%
started a new career after completing these courses
26%
got a tangible career benefit from this course
Flexible deadlines
Reset deadlines in accordance to your schedule.
Shareable Certificate
Earn a Certificate upon completion
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Course 2 of 5 in the
Approx. 6 hours to complete
English
Subtitles: Arabic, French, Portuguese (European), Italian, Vietnamese, German, Russian, English, Spanish
What you will learn
Describe the various roles that make up a Data Science team
Manage a Data Science team onboarding
Know relevant questions for interviewing data scientists
Understand how to encourage and empower Data Science teams
Skills you will gain
Team BuildingData ScienceManagementTeam Management
Learner Career Outcomes
35%
started a new career after completing these courses
26%
got a tangible career benefit from this course
Flexible deadlines
Reset deadlines in accordance to your schedule.
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Course 2 of 5 in the
Approx. 6 hours to complete
English
Subtitles: Arabic, French, Portuguese (European), Italian, Vietnamese, German, Russian, English, Spanish
Offered by
Johns Hopkins University
The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.
Syllabus - What you will learn from this course
6 hours to complete
Building a Data Science Team
Welcome to Building a Data Science Team! This course is one module, intended to be taken in one week. the course works best if you follow along with the material in the order it is presented. Each lecture consists of videos and reading materials and every lecture has a 5 question quiz. You need to get 4 out of 5 or better on the quiz to pass. Overall the quizzes are worth 17% of your grade each, with the exception of the last quiz, which is worth 15%. I'm excited to have you in the class and look forward to your contributions to the learning community. Click Discussions to see forums where you can discuss the course material with fellow students taking the class. Be sure to introduce yourself to everyone in the Meet and Greet forum.If you have questions about course content, please post them in the forums to get help from others in the course community. For technical problems with the Coursera platform, visit the Learner Help Center.Good luck as you get started, and I hope you enjoy the course! -Jeff
6 hours to complete
17 videos (Total 83 min), 8 readings, 6 quizzes
Reviews
TOP REVIEWS FROM BUILDING A DATA SCIENCE TEAM
by NNDec 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.
by PVJan 22, 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 SMJan 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.
by RVMay 21, 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.
About the Executive Data Science Specialization
Assemble the right team, ask the right questions, and avoid the mistakes that derail data science projects.
Frequently Asked Questions
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