Objective 1.1 Identify the Project Scope CERTIFIED-DATA-SCIENCE-PRACTITIONER Practice Questions (Page 1)

Questions 1–5

1. 1foundation · easy

   What is the primary purpose of defining milestones in a data science project timeline?

   • ATo define the project's success metrics
   • BTo identify the project's stakeholders
   • CTo allocate the project budget
   • DTo track progress and ensure the project stays on schedule
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2. 2application · medium

   A bank is developing a credit risk model. The project has a regulatory deadline in 4 months. The data science team has identified that the data quality is poor and will require significant cleaning. The team also needs to coordinate with the IT department to access the data. What is the best way to structure the project timeline?

   • ABreak the project into phases with milestones for data access, data cleaning, model development, and validation, each with a buffer.
   • BSet a single deadline for the final model and work backward, allocating time equally to each task.
   • CAsk the IT department to provide the data immediately and assume the cleaning will be straightforward.
   • DStart with model development immediately and clean the data later if time permits.
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4. 3foundation · easy

   In the context of defining project specifications, what is the primary purpose of identifying key performance indicators (KPIs)?

   • ATo assign tasks to team members
   • BTo document the data sources used in the project
   • CTo measure the success of the project against its objectives
   • DTo outline the project timeline and milestones
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5. 4application · medium

   A logistics company is building a demand forecasting model. The project has a hard deadline in 6 weeks for a seasonal promotion. The data science team estimates that data cleaning will take 2 weeks, model development 3 weeks, and validation 1 week. However, the data engineering team has not yet confirmed access to the historical sales data. What is the most appropriate timeline determination?

   • AAdd a 2-week buffer to the entire project, making the timeline 8 weeks, and ignore the original deadline.
   • BReduce the validation phase to 2 days to ensure the deadline is met, regardless of data availability.
   • CCreate a milestone at the end of week 1 to confirm data access, and adjust the subsequent schedule if the data is delayed.
   • DAssume the data will be available on time and schedule the model development to start immediately.
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6. 5foundation · easy

   Which of the following best defines a project specification in a data science project?

   • AA description of the technical architecture and infrastructure
   • BA detailed list of all data sources and their schemas
   • CA schedule of tasks and milestones for the project team
   • DA clear statement of objectives, success metrics, and stakeholder requirements
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