About this 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

Created by: Johns Hopkins University

Taught by: Jeff Leek, PhD, Associate Professor, Biostatistics
Bloomberg School of Public Health
Taught by: Brian Caffo, PhD, Professor, Biostatistics
Bloomberg School of Public Health
Taught by: Roger D. Peng, PhD, Associate Professor, Biostatistics
Bloomberg School of Public Health

Basic Info	Course 2 of 5 in the Executive Data Science Specialization
Commitment	1 week of study, 4-6 hours
Language	English
How To Pass	Pass all graded assignments to complete the course.
User Ratings	4.5 stars Average User Rating 4.5See what learners said

Syllabus

WEEK 1

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

17 videos, 8 readings

Video: About your instructor
Video: The Data Team
Video: When Do You Need Data Science?
Reading: Lecture materials and related reading
Video: Data Engineer: Qualifications & Skills
Video: Data Scientist: Qualifications & Skills
Video: Data Science Manager: Qualifications & Skills
Reading: Lecture Materials and Related Reading
Video: Where To Find The Data Team
Video: Interviewing For Data Science
Reading: Lecture Materials and Related Reading
Video: Onboarding the Data Science Team
Video: Managing the Data Science Team
Video: Evaluating Success of the Team
Reading: Lecture Materials and Related Reading
Video: Embedded Teams vs. Dedicated Groups
Video: How Does Data Science Interact with Other Groups
Video: Empowering Others to Use Data
Reading: Lecture Materials and Related Reading
Video: Common Interaction Difficulties
Video: Common Internal Difficulties
Reading: Lecture Materials and Related Reading
Video: Wrap-Up
Reading: Lecture Materials and Related Reading
Reading: Post-Course Survey

Graded: Defining the data science team

Graded: Data team qualifications

Graded: Assembling the team

Graded: Management strategies

Graded: Working with other teams

Graded: Common difficulties

FAQs

How It Works

Coursework

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Creators

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.

Pricing

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Ratings and Reviews

Rated 4.5 out of 5 of 1,245 ratings

Esta serie de cursos, es recomendable para iniciar en la carrera de Ciencia de Datos, conceptos claros, expuestos por catedráticos de primer nivel

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.

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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.