Data Science Project Management Group Course

Deliver Better Team Outcomes

Learn the nuances of data science project management with your team.


4 Ways to Grow as a Team

License On-Demand Content

Looking to Provide Training Materials to Hundreds? Enterprises (corporate or academic institutions) can provide bulk licenses to the Data Science Team Lead Foundations course to empower its workforce.

The Data Science Team Lead Foundations™ (DS-TLF) gives a large group of members (or even the entire organization) access to 6.5 hours of on-demand videos, exercises, the case study, and curated papers at a deeply discounted price. Students will learn key collaboration frameworks (ex. Scrum, Kanban, Data Driven Scrum) as well as data science workflows (ex. CRISP-DM, OSEMN).

Learn How to Implement a Process

Searching for an Instructor-Led Course? Enable your team to be more productive by understanding appropriate data science processes for your team.

The Data Science Team Lead™ (DS-TL) course includes all of the content from the DS-TLF course plus actionable training via live sessions. The course structure can be through four weekly sessions, two half-day seminars, or one full-day seminar.

These mentoring sessions will help ensure you fully understand how to use the collaboration frameworks (ex. Scrum, Kanban, Data Driven Scrum) and data science workflows (ex. CRISP-DM, OSEMN).

Implement the Knowledge as a Team

Want to Dive Deeper? Define and implement an appropriate data science workflow and collaboration framework for your situation.

Our Data Science Team Lead Plus™ (DS-TL+) course includes all the content in our DS-TL course plus extended consulting and mentoring sessions to help you confidently define and execute a well-defined repeatable process within an organization. It has 8.5 hours of total on-demand videos.

This will help you define and implement a data science team process for your organization. It also explores best practices to launch and execute a data science project (ex. project initiation, kickoffs, overcoming common issues,…).

data science project management training

Organize Customized Classes

Have a Specific Training Need? Some organizations request a customized course focused on a specific deep-dive from the broader courses. These include:

  • Data science for strategic leadership
  • Ethical AI
  • Data science product strategy
  • Structuring a data science PMO

Modalities can be structured as a 2-day class, daily live sessions with online learning (e.g., videos) in between sessions, or a one-month class that meets weekly (with asynchronous online learning in between sessions).

Empower Your Team to Deliver Better Results

Deliver Better Insights Faster
Build an agile culture of rapid delivery focusing on the most promising insights.

Drive Efficiency
Adopt repeatable processes to improve team efficiency.

Avoid Pitfalls
Identify and address common project challenges.

Build Happier Teams
Boost team morale through the use of more effective processes.

Enhance Collaboration
Improve stakeholder communication and help scale projects across teams.

Leverage Expertise
Learn from instructors who live-and-breath this stuff.

Who should Enroll?

There is no specific background or prior experience required. In fact, alumni come from over 20 different countries with experience ranging from senior executives to junior data scientists, with a range of roles, including:

  • Data scientist
  • Project manager
  • Data engineer
  • Software engineer
  • Business analyst
  • IT manager
  • Scrum master
  • CEO
  • Product owner
  • Consultant
  • Data Analyst
  • Intern

What you get…

Team Coaching Sessions (except Foundations)

On-demand Video Lectures

Real-world Application (Case Study)

Curated Blogs, Whitepapers, and interactive Games

Exclusive Training on Data Driven Scrum

Optional Certification

Module Descriptions

Modules 5 and 6 are only in DSTL+

Data Science, Agility & Teams

Course Overview
  • About Us
  • Exploring the Need for Process
  • Data Science vs Software Engineering
  • Process Benefits & Adoption
  • Our View of Data Science
  • Intro to Agile Data Science
  • Why Agility is Important
  • Agile Data Science Benefits
  • How to Achieve Agility
Data Science Teams
  • Exploring Team Roles
  • Non-technical Roles
  • Data Science Project Teams
  • Adopting a Process (Paper)
Case Study
  • Case Study Overview
  • Case Details (Paper)
  • Module Sythesis (Case Questions)
One-on-One Session with Mentor (DSTL or DSTL+)

The Data Science Life Cycle

Life Cycles Overview
  • Module Overview
  • Types of Frameworks
  • CRISP-DM Overview
  • CRISP-DM Challenges
  • CRISP-DM Guide (Reading)
Other Frameworks
  • Harvard's Workflow
  • Domino's Life Cycle
  • Uber's Process
  • Microsoft's TDSP
Review and Reflection
  • Workflow Review
  • Workflow Discussion
  • Workflow & Responsible AI
  • Blog Reflection
  • Module Synthesis (Case Questions)
One-on-One Session with Mentor (DSTL or DSTL+)

Team Collaboration

Collaboration Overview Lean and Kanban
  • Lean Overview
  • Kanban Overview
  • Kanban for Data Science
  • Kanban Evaluation
  • Scrum Values and Principles
  • Scrum Key Concepts
  • Scrum for Data Science
  • Scrum Discussion
  • Scrum Guide (Reading)
Review and Reflection
  • Collaboration Framework Blog Reflection
  • Module Synthesis (Case Questions)
One-on-One Session with Mentor (DSTL & DSTL+)

Data Driven Scrum & Special Topics

Data Driven Scrum
  • Overview
  • Workflow
  • Artifacts, Roles, and Meetings
  • DDS Increments
  • Example Project using DDS
  • Combining DDS & CRISP-DM
  • DDS Guide (reading)
Special Topics
  • Project Simulation Game I
  • Project Simulation Game II
  • Comparing Frameworks
  • Project Metrics
  • Metrics Discussion
  • An Agile Team's Journey (Paper)
  • Module Synthesis (Case Questions)
One-on-One Session with Mentor (DSTL & DSTL+)
*Team Lead+ Course Only

Projects, Programs, Products, & Prioritization

Managing Multiple Efforts
  • Program Management
  • Scaling Agile Teams
  • Scaling Data Science Teams
Data Science Products
  • Intro Word Game
  • Product Management
  • Product Owner
  • Product Manifesto
  • Why Prioritize?
  • Prioritization Framework
  • Prioritization Discussion
  • Value Assessment Workshops
Case Study
  • Module Sythesis (Case Questions)
One-on-One Session with Mentor
*Team Lead+ Course Only

Define & Use a Framework

Extended 3-week Mentoring Sessions to Implement a new Process
  • Module Intro
  • How to Select a Team Process
  • Process Selection Discussion
  • How to Define a Process
  • Overcoming Common Issues I
  • Overcoming Common Issues II

Take the 30-minute, multiple-choice exam.

Upon passing, you will receive the appropriate lifetime Data Science Team Lead Certificate and LinkedIn Badge.

You will have lifetime access to the online course portal which includes up-to-date training material.

What our Students are Saying…

“I would recommend the course as it gives you the conceptual frameworks to think constructively on how to better organize data science work within your organization.”


“Great to have discussions with someone who thinks from a methodological perspective, but also has hands-on experience with managing data science work. Also, I enjoyed the discussions in the videos between the course instructors.”

Jelle De Jong

Principal Consultant at Quantitative Business Consulting – Netherlands

“This course was very helpful, in that it refreshed my memory on SCRUM and indeed its limitations and benefits as well as introduced some methods I’d not considered before.”

“I enjoyed it all to be honest. Focusing on real life and workflows was important to me as its great knowing a theory but how do you implement and use is always the killer part.”

Mark Bonnett

Scrum Master / Program Manager – Independent Consultant UK and Saudi Arabia

“I highly recommend this course. It focuses on essential skills that I immediately put to work on a data science project.”

“I tell my friends and peers – Take this class for the insights it adds to your project toolkit.”

Vince Plaza

Principal Consultant at Plaza Consulting, Inc. – USA

“This course helped me understand how a data science team should think and I came out of the course with a better understanding of how to tackle data science project management problems.”

“I liked that there was offline work that could be done at own free time, combined with live discussions that were very friendly and helpful.”

Xavier Leow

Technical Project Manager at Shopee – Singapore

“Understanding the course content was helpful, but the real value-add we experienced was the 1-on-1 sessions with the DSPA team; it’s how we learned ways to apply the course content to our unique work environment.”

“Implementing the suggestions we got from the DSPA team has helped us set more reasonable expectations for how we should manage projects and helped us develop a roadmap toward doing this better.”

Daniel Miller

Project Manager at Pandata – USA

“The course was extremely useful. My only regret is not having taken it sooner. The format was surprisingly easy to follow. Short lectures, followed by interesting discussions amongst the lecturers, made the material very easy to digest.”

“The best part of the course was probably the weekly one-on-one interactions with the lead trainer, which were extremely useful.”

Dr Thibaut Jombart

Senior Data Scientist – World Health Organization (WHO). Associate Professor in Outbreak Analytics – London School of Hygiene and Tropical / Imperial College London

“As a Scrum Master, the DSPA Team Lead course helped me to look at what I do from different viewpoints. I now not only have a better understanding of how developers look at the Agile process, but also how Data Scientists look at the Agile process.”

“This new understanding will help me to better run my Teams and run different types of Teams. What I liked best, and helped me the most, was the one on one aspect of the course. Our weekly sessions helped me to ask questions that I would not have been able to via e-mail.”


Joe Acquavella

Scrum Master at CACI International Inc – USA

“The course was very useful. It covered both the theoretical and practical aspects of Data Science Project Management. The training also validated my belief that our software development efforts are different than our data science efforts, which means that our data science projects should have a different process than our software development team process.”

“The mentoring sessions were very valuable, as was the ability to go back over the material at any time.”

Hector Rangel

Consulting & Data Science lead at Arena Analytics – Mexico

For a deeper dive, explore our testimonial page and alumni interviews.

Frequently Asked Questions

  • Why is Data Science Project Management important?

    Little attention had gone toward data science project management as the spotlight focused on new technologies and capabilities. This has left data science teams struggling to know how to implement their projects (or maybe using a framework designed for software development). Organizations that effectively manage data science initiatives are more likely to see the benefits of their investments.

  • Why should we get training from the Data Science Process Alliance?

    We focus on one and only one topic (data science project management), and have expertise beyond other training services and consultancies. Specifically, we research and apply agile data science project management practices to educate others to effectively deliver data science project outcomes. Sure, we’re biased in stating this, but if you want to learn how to better manage data science projects, we’re the best option.

  • How do we register for a team-based course

    Contact Us for pricing – we can easily send one invoice for all your team members

  • What are the course prerequisites?

    There is no specific prerequisite knowledge required – but the team should be interested in improving the process they use to execute their projects.

  • What happens in the live mentor sessions?

    It’s your team’s time. We’ll flex to make it valuable for your team. Some teams enjoy having the Mentors answer specific questions from the content covered in that module. Others teams discuss relevant curated readings, and yet others prefer to use the time discussing how to apply the knowledge gained within their team.

  • How do we schedule the live mentoring sessions?

    After the team registers, we will work to find a time that works for the team one one or our mentors / instructors. We’re based in the USA, so European teams typically are scheduled during their afternoons (or evenings). Teams based in the Asia-Pacific region generally are lined up in their mornings (or late evenings). Teams in the Americas often have class during the workday (but some prefer evenings).

  • How long do the courses take?
    • Team Lead Foundations is self-paced. Some students finish in one week, others finish in three months. Most students invest 6 – 12 hours in the course.
    • Team Lead is designed as a 4-week course. Generally, the student takes one module per week and finishes each week with their one-on-one session but some students have taken the course as an accelerated 2-week course. Most students invest 8 – 16 hours in the course.
    • Team Lead Plus is designed as an 8-week course. Generally, the student takes one module per week and finishes each week with their one-on-one session (but just as with the TL course, this can be adjusted). Most students invest 12 – 30 hours in the course.
  • For how long can we access the course content?

    You’ll have life-time access.

  • Find Out More – Contact Us to Advance your Team