Building a Data Science Team (Coursera)

Building a Data Science Team (Coursera)

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.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

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

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

Course 2 of 5 in the Executive Data Science Specialization.

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. Good luck as you get started, and I hope you enjoy the course! -Jeff

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Data Science for Business Innovation (Coursera) Coursera
Politecnico di Milano,EIT Digital

Data Science for Business Innovation (Coursera)

The course is a compendium of the must-have expertise in data science for executive and middle-management to foster data-driven innovation. It consists of introductory lectures spanning big data, machine learning, data valorization and communication. Topics cover the essential concepts and intuitions on data needs, data analysis, machine learning methods, respective pros and cons, and practical applicability issues.

Sep 21st 2026
4 Weeks
Leadership in 21st Century Organizations (Coursera) Coursera
Copenhagen Business School

Leadership in 21st Century Organizations (Coursera)

Meet Jim Barton, the new CEO of Santa Monica Aerospace. Jim's job won't be easy: the company's hemorrhaging cash, struggling to regain investors' trust after an accounting scandal, and striving to transform its culture to become a more global competitor. In this course, you’ll travel with Jim as he takes on leadership challenges ranging from strategy execution, to inspiring people, to maintaining an ethical approach. Experts agree that twentieth-century leadership practices are inadequate for the stormy twenty-first-century present.

Sep 21st 2026
5-12 Weeks
Understanding China, 1700-2000: A Data Analytic Approach, Part 2 (Coursera) Coursera
The Hong Kong University of Science and Technology - HKUST

Understanding China, 1700-2000: A Data Analytic Approach, Part 2 (Coursera)

The purpose of this course is to summarize new directions in Chinese history and social science produced by the creation and analysis of big historical datasets based on newly opened Chinese archival holdings, and to organize this knowledge in a framework that encourages learning about China in comparative perspective. Our course demonstrates how a new scholarship of discovery is redefining what is singular about modern China and modern Chinese history.

Sep 28th 2026
4 Weeks
Practical Predictive Analytics: Models and Methods (Coursera) Coursera
University of Washington

Practical Predictive Analytics: Models and Methods (Coursera)

Statistical experiment design and analytics are at the heart of data science. In this course you will design statistical experiments and analyze the results using modern methods. You will also explore the common pitfalls in interpreting statistical arguments, especially those associated with big data. Collectively, this course will help you internalize a core set of practical and effective machine learning methods and concepts, and apply them to solve some real world problems.

Sep 14th 2026
4 Weeks
Avoiding AI Harm (Coursera) Coursera
Fred Hutchinson Cancer Center

Avoiding AI Harm (Coursera)

This course is designed for those in roles with decision making power, to help them understand major topics to consider for using and developing Artificial Intelligence (AI) responsibly, including popular Generative AI tools like ChatGPT and others. It covers real-world examples of situations where AI was used in variety of fields and situations in ways hat revealed ethical concerns. Strategies are suggested to avoid doing harm working with AI, including a framework for working responsibly with AI.

Sep 21st 2026
1 Week
Tools and Practices for Addressing Pandemic Challenges (Coursera) Coursera
Politecnico di Milano

Tools and Practices for Addressing Pandemic Challenges (Coursera)

An overview of the tools, techniques, and practices that can be enacted by policy makers, countries, and organizations to monitor, manage, and react to pandemics and mitigate and govern their impacts. An introductory, multidisciplinary course covering data science, social science, healthcare, and management, paving the way to various courses on specific matters.

Sep 28th 2026
2 Weeks
Code Free Data Science (Coursera) Coursera
University of California, San Diego

Code Free Data Science (Coursera)

The Code Free Data Science class is designed for learners seeking to gain or expand their knowledge in the area of Data Science. Participants will receive the basic training in effective predictive analytic approaches accompanying the growing discipline of Data Science without any programming requirements. Machine Learning methods will be presented by utilizing the KNIME Analytics Platform to discover patterns and relationships in data.

Sep 28th 2026
4 Weeks
Machine Translation (Coursera) Coursera
Karlsruhe Institute of Technology - KIT

Machine Translation (Coursera)

Welcome to the CLICS-Machine Translation MOOC. This MOOC explains the basic principles of machine translation. Machine translation is the task of translating from one natural language to another natural language. Therefore, these algorithms can help people communicate in different languages. Such algorithms are used in common applications, from Google Translate to apps on your mobile device.

Sep 28th 2026
5-12 Weeks
Hands-on Text Mining and Analytics (Coursera) Coursera
Yonsei University

Hands-on Text Mining and Analytics (Coursera)

This course provides an unique opportunity for you to learn key components of text mining and analytics aided by the real world datasets and the text mining toolkit written in Java. Hands-on experience in core text mining techniques including text preprocessing, sentiment analysis, and topic modeling help learners be trained to be a competent data scientists.

Sep 21st 2026
5-12 Weeks