Practitioner Course Overview

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Course Benefits

Be part of a team that will:

  • Improve actionable insight via better communication with stakeholders
  • Increase your team’s effectiveness via enhanced team coordination
  • Drive process efficiency and the exploration of high value analyses

Who Should Attend

The Data Science Practitioner™ (DSP) provides an overview of data science project management. The course is for anyone who wants to gain an understanding of how to be part of an effective data science team. This includes members of data science teams, product owners, managers, and process masters.

By taking this course, you will gain an high level understanding of how using a data science process can improve a data science team’s effectiveness in generating actionable insight.

In short, the course will be useful for anyone who would like to start learning how to execute agile data science projects and be an effective member of a data science team (or how to work with a data science team).

What You Will Learn

The key focus of the course is to understand:

  • Agility within a data science project context
  • Data Science Life Cycle frameworks
  • Data Science collaboration frameworks

How You Will Learn

  • Online modules (videos and some readings)
  • On-demand support from DSPA instructors (via email)
  • Online review material for the certification exam

Course Objectives

After this course, you will be able to:

  • Describe the key differences between data science projects and software development projects
  • Explain what is a data science life cycle
    (data science workflow)
  • Articulate the phases defined within CRISP-DM 
  • Explain the importance of team coordination frameworks
  • Articulate the key aspects of Kanban, Scrum, and Data Driven Scrum
  • Explain why agility is important for data science projects

Course Modules

Need for Improved Process:

  • Benefits of improved team process
  • Why not Software Development processes
  • Workflow and coordination frameworks
Data Science Workflows:

  • Understanding the Data Science Life Cycle
  • Workflow Frameworks (CRISP-DM and TDSP)
  • Iterations (and how to “loop back”)
Data Science Process Frameworks:

  • Planing and Prioritizing tasks
  • Agile frameworks (Scrum, DDS)
  • Lean principles (Kanban)
Agility and Data Science:

  • What is Agile Data Science?
  • The need  for Agility
  • The benefits of Agility

Access the DSPA Community

When you enroll in our Data Science Practitioner™ (DSP) training, you immediately become a member of our community, which is a dynamic space that:

  • Connects you directly with your peers
  • Enables access to exclusive events
  • Provides a library of curated data science project management related resources (e.g., white papers)

In addition, you will also be able to tap into our community of learners, Data Science Team Leads, and DSPA instructors. This professional network enables you to find answers when you need advice.

Member Feedback

DSPA is very unique and very useful – I haven’t seen any other similar certifications.

– Greg G.

“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 P.

Get a Course Brochure

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The cost of $295 includes access to the DSPA community, Practitioner training materials, the DSP live seminar and the DSP Certification Exam