Data Science Process Professional™ Training

The Data Science Process Professional™ (DSPP) course provides training for organizations, consultants, and students wanting to understand and experience how to effectively work in a data science team by providing the foundational knowledge required to effectively use a data science process in a highly practical way.

The course is a combination of instruction and team-based exercises where students experience how using a data science processes can improve a data science team’s effectiveness in generating actionable insight.

The course also includes registration for the Data Science Process Professional certification exam.

What you Learn

  • Foundational Agile concepts and how they help or hinder data science projects

  • How to integrate fairness, transparency, and model validation within a project

  • Knowledge of the potential frameworks, such as:
    • Scrum framework and how it can be applied within a data science context
    • The Kanban framework and how it can be applied within a data science context
    • CRISP-DM and how it can be applied within a data science context
    • Emerging data science frameworks (TDSP, DataDrivenScrum)

  • Enable the successful execution of data science effort by knowing:
    • When to select which framework (or set of frameworks) for your data science project
    • How to define a project’s vision, scope and actionable insight goals
    • How to identify stakeholders and success criteria
    • How to define the roles required within a data science project
    • How to select and use the appropriate tools for the desired framework

  • Maximize the results of a data science project by knowing how to:
    • Create, plan and conclude an iteration that adheres to the selected team framework
    • Communicate to stakeholders and other team members
    • Identify and manage impediments and project risks
    • Interface with teams that use other frameworks
    • Determine the best approach to test / validate the insights generated

Course Format

The course is either a 2-day face-to-face class, or a one month web-based class that meets weekly for synchronous discussions and exercises (as well as online learning in between sessions).

In both formats, during the class, students work on real-life cases, participate in discussions with other students (that are instructor facilitated), and have readings to compliment the discussions.

The course exposes common missteps and misunderstandings, so students gain an awareness of the associated symptoms of those missteps. The course also provides prescriptive guidance to avoid having the project go off track from those missteps and misunderstandings.

Course Modules

Agility and Data Science:

  • What is Agile Data Science?
  • Software Development vs Data Science?
  • Roles (Product Owner, Process Expert, Data Engineer, …)
Data Science Workflows:

  • Project phases – using workflows such as CRISP-DM, OSEMN
  • Project phases and iterations (how to “loop back”)
  • Creating a series of experiments
Data Science Process Frameworks:

  • Planing and Prioritizing experiments
  • General Agile frameworks (Kanban, Scrum)
  • Data Science Agile Frameworks (TDSP, and Data Driven Scrum)
Project Management Considerations:

  • Tools, Testing, Metrics, Growing teams,
  • Model / Data versioning
  • Coordinating across projects


The price of the course, when delivered online, is $900 plus an additional $50 testing and certification fee. 

For face-to-face residential courses, the cost of the class is $1,440 plus an additional $50 testing and certification fee.