Data Science Project Management Course

Deliver Better Data Science Outcomes.

Data Science Projects are unique.
It’s time to start managing them as such.


Confidently Lead Data Science Projects

The Project Management Course for Data Science

The Data Science Team Lead™ (DSTL) course provides in-depth, comprehensive, and actionable training to empower you to confidently lead data science projects.

Help your team deliver better results by understanding how to implement collaboration frameworks (Scrum, Kanban, Data Driven Scrum), data science workflow frameworks (CRISP-DM, OSEMN) and exploring methodologies from Uber, Domino, and Harvard.

Learn data science project management (NOT software project management)!

Offered in both individual or private group class formats.

Why take the Course?

Improve your data science project leadership and 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.

Be Data Science Focused:
Implement processes that work best for data science projects.

Enhance Collaboration:
Improve stakeholder engagement and help scale projects across teams.

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

Who should enroll?

Individual professionals who are leading (or are looking to lead) data science projects and teams should enroll directly. If you represent an organization with four or more people looking for training, then contact us to learn about the private group course options. Some companies stick with the standard DSTL curriculum while others prefer customized material.

There is no specific background or prior experience required. In fact, alumni come from over 15 different countries with experience ranging from senior executives to full-time students, with a range of roles, including:

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

What you get…

4 one-on-one Customized Coaching Sessions

6+ hours of on-demand Video Lectures

Real-world Application (Case Study)

Curated Blogs, Whitepapers, and interactive Games

Exclusive Training on Data Driven Scrum

Lifetime Certification and Portal Access

Course Modules

Data Science, Agility & Teams

Course Overview
  • About Us
  • Exploring the Need for Process
  • Data Science vs Software Engineering
  • Selecting a Process
  • 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 & Synthesis
  • Case Study Overview
  • Case Details (Paper)
  • Module Sythesis (Case Questions)

One-on-One Session with Mentor

The Data Science Life Cycle

Life Cycles Overview
  • Module Overview
  • Types of Frameworks Lecture
  • Types of Frameworks Discussion

  • 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 Blog Reflection
  • Module Syntehsis (Case Questions)

One-on-One Session with Mentor

Team Collaboration

Collaboration Frameworks Overview
  • Module 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

Data Driven Scrum & Special Topics

DDS & Special Topics Overview
  • Module Overview

Data Driven Scrum
  • Overview
  • Workflow
  • Artifacts, Roles, and Meetings
  • Example Project using DDS
  • DDS Guide (reading)
Special Topics
  • Project Simulation Game I
  • Project Simulation Game II
  • Comparing Frameworks
  • How to Select a Team Process
  • Discussion on Selecting a Process
  • How to Measure a DS Project?
  • Discussion on Metrics
  • Overcoming Common Issues
  • Overcoming Common Issues II
  • A Team's Agile Journey (Paper)
  • Module Synthesis (Case Questions)

One-on-One Session with Mentor

Review some final pointers from the instructors

Sit the 30-minute, multiple-choice exam.

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

You will have lifetime access to the online 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.

Find Out More – Get Our Brochure

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Frequently Asked Questions

  • Why get Trained from the Data Science Process Alliance

    Because we’ve decided to focus on one and only one topic that is beyond the true expertise of other training services and consultancies. Namely, 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.

  • What happens in the One-on-One Mentor Sessions?

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

  • How long does the Course take?

    Duration: It’s designed as a 4-week course. Generally, the student takes one module per week and finishes each week with their one-on-one session. Most students take the certification exam within days of their fourth and final one-on-one session. However, we’ll adjust to meet your schedule. Some students have taken it as an accelerated 2-week course. The longest so far has been 6 weeks.

    Total Time Investment: Students tend to invest 16 – 32 hours in the course. A typical breakdown is:

    • 6 hours for the on-demand videos
    • 4 – 10 hours for re-referencing/re-watching the videos
    • 3 – 8  hours for activities, case study, and readings
    • 2 hours for the 4 one-on-one sessions (30 min each)
    • 1 – 6 hours to study and sit the exam
  • Can I train with my Team?

    Yes. We could do the traditional one-on-one sessions with your peers or lead a private group class. Either way, ask us about group discounts.

    If you are already a Data Science Team Lead, then you have some additional options:

    • Use the course material to lead the training. Some Team Leads do this on their own while others seek ongoing support from a Data Science Process Alliance mentor.
    • Have your team members enroll in the Data Science Practitioner course. This is a short course exclusively for organizations with at least Data Science Team Lead who would like higher-level training (4 – 8 hours) for their peers.
  • How do I register? And what happens next?

    You can register using the button just below this FAQ (or at the top of this page).  After that, you’ll have access to the course contents. A mentor will reach out to you schedule your one-on-one sessions.

  • What does the Course cost?

    $950. Ask for group discounts or discounts for full-time students.

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