Answers to Frequently Asked Questions

Why Get Certified
Certification Information
Training Information
Why Get Certified
    • Why Get Certified?
      In short, DSP certified team members help to maximize the value of an organization’s data science efforts via the use of a well-defined, repeatable process. Furthermore, people who obtain DSP certification:
      (1) Expand their career opportunities (by improving their marketability)
      (2) Demonstrate to employers their knowledge of data science process frameworks
      (3) Engage with a community of recognized data science process experts
    • Why is using a well-defined, repeatable process important?
      There is an enormous amount of research, including case studies of real teams, that demonstrate the value of using a well-defined, repeatable process. Adopting an improved process framework will help to:
      - Ensure a team’s insights are valid
      - Improve the efficiency of that team
      - Improve the actionable insight generated from the project
    • What frameworks / process / methodologies are included in the training and certification exam?
      All the applicable frameworks are covered, including Scrum, Kanban, DataDrivenScrum, TDSP (Microsoft’s Team Data Science Process), and CRISP-DM.
    • Why is selecting a framework difficult? Why do I need to learn about all these frameworks? Shouldn’t I just pick the best one?
       Part of the challenge is that while there are many possible frameworks, each have challenges when using within a data science context. In short, when a team does decide to use a process framework, which framework (or combination of frameworks) should be used? Should a team use CRISP-DM? Scrum? Kanban? a newer such as TDSP? Or a hybrid of these? Each of these frameworks have advantages and disadvantages, and hence, the “best” framework depends on many factors (e.g., type of data science project, size of team, background of team, expectations within the organization). Furthermore, some frameworks, like TDSP, leverage aspects other frameworks (e.g., Scrum, CRISP-DM), and so, implicitly require knowledge of those other frameworks.
    • Where can I find out more about these frameworks prior to enrolling in the course?
      There are many web sites that discuss using one of these frameworks within a data science context. However, the web site that focuses on all these frameworks, within a data science context, is www.datascience-pm.com
Certification Information
    • Will my current / future employer (or client) know about (and value) this certification?
      While the certification is gaining name recognition and the value of the certification is becoming increasingly clear within and across organizations, not all organizations are aware of the certification or even the value of using a well-defined process. However, having this certification on your resume will typically encourage your current / future employer / client to ask about the certification, which provides a way to discuss how your skills in this area are critical to the success of the project.
    • Do I need to take your training to take the certification exam?
      No, you can take the exam without enrolling in our course. However, for many people, enrolling in our training course is the most efficient way to gain the knowledge required to pass the exam.
Training Information
    • How much time does the training take?
      For our online course, the training lasts 4 weeks, and you will spend between 3 – 5 hours per week on the course. For our intensive face-to-face courses, the training lasts 2 days.
    • Is it possible to train our entire team in a private face-to-face intensive (or 6-week online) course?
      Yes! Having a team take the training together is the best way to ensure the entire team has the appropriate knowledge to help ensure a successful project. Please contact us for details, including the ability to customize the training for your organization’s needs.

  • When does the next course start?
    Courses start frequently, please contact us to explore when it makes sense for you to start.