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Roger D. Peng, PhD,
Jeff Leek, PhD,
and
Brian Caffo, PhD
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.
Read more
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.
Read more
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
Register for this course and see more details by visiting:
OpenCourser.com/course/utlm9w/building
What's inside
Syllabus
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
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Covers data science team organization and management, which is a critical skill for data science executives
Taught by Dr. Roger D. Peng, Dr. Jeff Leek, and Dr. Brian Caffo, who are recognized for their work in data science
Covers the roles, qualifications, and onboarding of data science team members, which is essential for building a successful team
Provides guidance on managing and empowering data science teams, which is crucial for their success
Suitable for data science executives and leaders looking to build and manage their teams effectively
Requires a basic understanding of data science concepts, which may be a limitation for absolute beginners
Save this course
Save Building a Data Science Team to your list so you can find it easily later:
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Reviews summary
Practical guide for managers
Learners say "Building a Data Science Team" is a well-received course that outlines the different roles of a data science team. It explains what to look for in when recruiting, strategies for managing, and tips for effective communication. Concepts are explained simply using real life examples. Reviewers say the course is a must-take for managers, especially those who are new to managing data science teams. It is recommended for those already in management who need a review of essential concepts.
Provides tips on recruiting data scientists.
"what to look for in data scientists"
"Building a Data Science Team is the second course in “Executive Data Science” specialization offered by John Hopkins University on Coursera. It is a one-week course that defines the different data science roles in an organization, what to look for in data scientists and strategies for managing and communicating with data scientists."
Provides tips for communicating with data scientists.
"strategies for managing and communicating with data scientists"
"present best practices in team building while specific to data science personel"
Offers strategies for effectively managing a data science team.
"strategies for managing and communicating with data scientists"
"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"
"Great content.It explains very simple the things you will require if your are planning to create a team of data analytics."
Concepts are explained using real life examples.
"Very useful course for data managers on how to build, empower, support teams and communicate with them.. Not the usual statistics or quants, but real life scenarios at work places beautifully brought out by someone who must have experienced them."
Explains the different roles of a data science team including analyst, engineer, and manager.
"defines the different data science roles in an organization"
"Like understaing the roles of analyst, engineer and manager"
"Its an exceptional course. A must pursue course for every manager either as new learning or refresher of knowledge.A great thanks to course trainers. Their teaching approach is very target oriented to put the concepts in student brain in simpler and efficient way."
Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Building a Data Science Team with these
activities:
Review data science team management principles
Show steps
Enhance your knowledge of data science team management principles to enhance your ability to lead and motivate your team to success.
Show steps
-
Review your notes or textbooks on data science management
-
Attend a workshop or webinar on data science team management
Practice interviewing data scientists
Show steps
Prepare for the process of interviewing data scientists by practicing common questions and scenarios.
Show steps
-
Review common data scientist interview questions
-
Practice answering these questions out loud
-
Conduct mock interviews with peers or colleagues
Develop a data science team management plan
Show steps
Create a comprehensive plan to guide the successful management of your data science team, improving your ability to build and lead a high-performing team.
Browse courses on
Team Management
Show steps
-
Identify the goals and objectives of your data science team
-
Define the roles and responsibilities of team members
-
Establish communication and collaboration protocols
-
Set up performance evaluation and feedback mechanisms
One other activity
Expand to see all activities and additional details
Show all four activities
Create a blog post or article on data science team management
Show steps
Solidify your understanding by writing a blog post or article that shares your insights and experiences in managing data science teams.
Browse courses on
Team Management
Show steps
-
Brainstorm ideas for a blog post or article on data science team management
-
Research and gather information on the topic
-
Write a draft of your blog post or article
-
Edit and revise your blog post or article
-
Publish your blog post or article on a relevant platform
Review data science team management principles
Show steps
Enhance your knowledge of data science team management principles to enhance your ability to lead and motivate your team to success.
Show steps
Show steps
Show steps
- Review your notes or textbooks on data science management
- Attend a workshop or webinar on data science team management
Practice interviewing data scientists
Show steps
Prepare for the process of interviewing data scientists by practicing common questions and scenarios.
Show steps
Show steps
Show steps
- Review common data scientist interview questions
- Practice answering these questions out loud
- Conduct mock interviews with peers or colleagues
Develop a data science team management plan
Show steps
Create a comprehensive plan to guide the successful management of your data science team, improving your ability to build and lead a high-performing team.
Browse courses on
Team Management
Show steps
Show steps
Show steps
- Identify the goals and objectives of your data science team
- Define the roles and responsibilities of team members
- Establish communication and collaboration protocols
- Set up performance evaluation and feedback mechanisms
One other activity
Expand to see all activities and additional details
Show all four activities
Create a blog post or article on data science team management
Show steps
Solidify your understanding by writing a blog post or article that shares your insights and experiences in managing data science teams.
Browse courses on
Team Management
Show steps
Show steps
Show steps
- Brainstorm ideas for a blog post or article on data science team management
- Research and gather information on the topic
- Write a draft of your blog post or article
- Edit and revise your blog post or article
- Publish your blog post or article on a relevant platform
Career center
Learners who complete Building a Data Science Team will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
Data Scientists analyze data to extract meaningful insights and patterns that can help businesses make informed decisions. This course can help you develop the skills needed to succeed in this role by providing a comprehensive overview of the data science process, from data collection and analysis to model building and deployment. You'll also learn how to communicate your findings effectively to stakeholders.
Data Analyst
Data Analyst
Data Analysts collect, clean, and analyze data to identify trends and patterns. This course can help you build a strong foundation in the principles of data science, including data analysis techniques, data visualization, and statistical modeling. You'll also learn how to use data analysis tools and technologies to extract meaningful insights from data.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design and implement machine learning models to solve business problems. This course can help you develop the skills needed to succeed in this role by providing a solid foundation in machine learning algorithms, model evaluation, and deployment. You'll also learn how to use machine learning tools and technologies to build and deploy machine learning models.
Data Engineer
Data Engineer
Data Engineers design and build data pipelines to collect, store, and process data. This course can help you develop the skills needed to succeed in this role by providing a comprehensive overview of the data engineering process, from data collection and storage to data processing and analysis. You'll also learn how to use data engineering tools and technologies to build and maintain data pipelines.
Business Intelligence Analyst
Business Intelligence Analyst
Business Intelligence Analysts use data to identify opportunities and solve problems. This course can help you develop the skills needed to succeed in this role by providing a comprehensive overview of the business intelligence process, from data collection and analysis to reporting and presentation. You'll also learn how to use business intelligence tools and technologies to extract meaningful insights from data.
Data Architect
Data Architect
Data Architects design and build data architectures to meet the needs of businesses. This course can help you develop the skills needed to succeed in this role by providing a comprehensive overview of the data architecture process, from data modeling and design to data governance and security. You'll also learn how to use data architecture tools and technologies to build and maintain data architectures.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. This course can help you develop the skills needed to succeed in this role by providing a comprehensive overview of the software development process, from requirements gathering and analysis to design, implementation, and testing. You'll also learn how to use software development tools and technologies to build and maintain software applications.
Product Manager
Product Manager
Product Managers are responsible for the development and success of products. This course can help you develop the skills needed to succeed in this role by providing a comprehensive overview of the product management process, from product planning and development to marketing and sales. You'll also learn how to use product management tools and technologies to manage and track the progress of products.
Project Manager
Project Manager
Project Managers are responsible for the planning, execution, and completion of projects. This course can help you develop the skills needed to succeed in this role by providing a comprehensive overview of the project management process, from project planning and initiation to project execution and closure. You'll also learn how to use project management tools and technologies to manage and track the progress of projects.
Data Warehouse Engineer
Data Warehouse Engineer
Data Warehouse Engineers design, build, and maintain data warehouses to store and manage data. This course can help you develop the skills needed to succeed in this role by providing a comprehensive overview of the data warehouse engineering process, from data modeling and design to data storage and management. You'll also learn how to use data warehouse engineering tools and technologies to build and maintain data warehouses.
Data Scientist Manager
Data Scientist Manager
Data Scientist Managers are responsible for leading and managing teams of data scientists. This course can help you develop the skills needed to succeed in this role by providing a comprehensive overview of the data science management process, from team building and management to project planning and execution. You'll also learn how to use data science management tools and technologies to manage and track the progress of data science teams.
Data Ethics Specialist
Data Ethics Specialist
Data Ethics Specialists are responsible for ensuring that data is used ethically and responsibly. This course can help you develop the skills needed to succeed in this role by providing a comprehensive overview of the data ethics process, from data collection and analysis to data use and dissemination. You'll also learn how to use data ethics tools and technologies to ensure that data is used ethically and responsibly.
Data Governance Analyst
Data Governance Analyst
Data Governance Analysts are responsible for developing and implementing data governance policies and procedures. This course can help you develop the skills needed to succeed in this role by providing a comprehensive overview of the data governance process, from data policy development and implementation to data compliance and enforcement. You'll also learn how to use data governance tools and technologies to manage and track the progress of data governance initiatives.
Data Privacy Analyst
Data Privacy Analyst
Data Privacy Analysts are responsible for ensuring that data is collected, used, and stored in accordance with privacy laws and regulations. This course can help you develop the skills needed to succeed in this role by providing a comprehensive overview of the data privacy process, from data protection and security to data breach response and recovery. You'll also learn how to use data privacy tools and technologies to ensure that data is collected, used, and stored in accordance with privacy laws and regulations.
Data Quality Analyst
Data Quality Analyst
Data Quality Analysts are responsible for ensuring that data is accurate, complete, and consistent. This course can help you develop the skills needed to succeed in this role by providing a comprehensive overview of the data quality process, from data collection and analysis to data cleansing and validation. You'll also learn how to use data quality tools and technologies to ensure that data is accurate, complete, and consistent.
For more career information including salaries, visit:
OpenCourser.com/course/utlm9w/building
Reading list
We've selected 12 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Building a Data Science Team.
Provides a comprehensive overview of machine learning, including the different types of machine learning algorithms, the different applications of machine learning, and the ethical implications of machine learning.
Provides a comprehensive overview of Bayesian reasoning and machine learning, including the different types of Bayesian reasoning algorithms, the different applications of Bayesian reasoning, and the ethical implications of Bayesian reasoning.
Provides a comprehensive overview of probabilistic graphical models, including the different types of probabilistic graphical models, the different applications of probabilistic graphical models, and the ethical implications of probabilistic graphical models.
Provides a comprehensive overview of information theory, inference, and learning algorithms, including the different types of information theory algorithms, the different applications of information theory, and the ethical implications of information theory.
Save
Provides a comprehensive overview of data mining, including the different types of data mining algorithms, the different applications of data mining, and the ethical implications of data mining.
Provides a comprehensive overview of statistical learning, including the different types of statistical learning algorithms, the different applications of statistical learning, and the ethical implications of statistical learning.
Save
Provides a comprehensive overview of deep learning, including the different types of deep learning algorithms, the different applications of deep learning, and the ethical implications of deep learning.
Provides a comprehensive overview of reinforcement learning, including the different types of reinforcement learning algorithms, the different applications of reinforcement learning, and the ethical implications of reinforcement learning.
Provides a comprehensive overview of data science, including the different roles in a data science team, the skills and qualifications required for each role, and the different types of data science projects.
Provides a hands-on introduction to data science, including how to collect, clean, and analyze data, and how to build and evaluate machine learning models.
Provides a gentle introduction to machine learning, including the different types of machine learning algorithms, how to train and evaluate machine learning models, and how to use machine learning to solve real-world problems.
Provides a comprehensive overview of artificial intelligence, including the different types of AI, the different applications of AI, and the ethical implications of AI.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/utlm9w/building
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Effort
1 week of study, 4-6 hours
Via
Coursera
Institution
Johns Hopkins University
Instructors
Roger D. Peng, PhD
Jeff Leek, PhD
Brian Caffo, PhD
Language
English
Transcripts
العربية
Français
বাংলা
українська мова
中文
Ελληνικά
Italiano
Português
tiếng Việt
Nederlands
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Deutsch
پښتو
اُردُو,
Pусский
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آذربایجان دیلی
Español
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қазақша
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magyar nyelv
Polski
This course belongs to a
collection
called
Executive Data Science. It's comprised of five courses:
- Managing Data Analysis
- Executive Data Science Capstone
- Data Science in Real Life
- Building a Data Science Team (viewing)
- A Crash Course in Data Science
Good to know
Covers data science team organization and management, which is a critical skill for data science executives
Taught by Dr. Roger D. Peng, Dr. Jeff Leek, and Dr. Brian Caffo, who are recognized for their work in data science
Covers the roles, qualifications, and onboarding of data science team members, which is essential for building a successful team
Provides guidance on managing and empowering data science teams, which is crucial for their success
Suitable for data science executives and leaders looking to build and manage their teams effectively
Requires a basic understanding of data science concepts, which may be a limitation for absolute beginners
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