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
- 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
- Exploring Team Roles
- Non-technical Roles
- Data Science Project Teams
- Adopting a Process (Paper)
- Case Study Overview
- Case Details (Paper)
- Module Sythesis (Case Questions)
The Data Science Life Cycle
- Module Overview
- Types of Frameworks
- CRISP-DM Overview
- CRISP-DM Challenges
- CRISP-DM Guide (Reading)
- OSEMN
- Harvard's Workflow
- Domino's Life Cycle
- Uber's Process
- Microsoft's TDSP
- Workflow Review
- Workflow Discussion
- Workflow & Responsible AI
- Blog Reflection
- Module Synthesis (Case Questions)
Team Collaboration
- 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)
- Collaboration Framework Blog Reflection
- Module Synthesis (Case Questions)
Data Driven Scrum & Special Topics
- Overview
- Workflow
- Artifacts, Roles, and Meetings
- DDS Increments
- Example Project using DDS
- Combining DDS & CRISP-DM
- DDS Guide (reading)
- Project Simulation Game I
- Project Simulation Game II
- Comparing Frameworks
- Project Metrics
- Metrics Discussion
- An Agile Team's Journey (Paper)
- Module Synthesis (Case Questions)
Projects, Programs, Products, & Prioritization
- Program Management
- Scaling Agile Teams
- Scaling Data Science Teams
- Intro Word Game
- Product Management
- Product Owner
- Product Manifesto
- Why Prioritize?
- Prioritization Framework
- Prioritization Discussion
- Value Assessment Workshops
- Module Sythesis (Case Questions)
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…
Jelle De Jong
“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
“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
“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
“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
“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
“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
“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
For a deeper dive, explore our testimonial page and alumni interviews.
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