PMI Cognitive project management in AI CPMAI Dumps in PDF

Free PMI CPMAI Real Questions (page: 1)

Your team is working on an NLP model and has just operationalized the first model. Your team makes updates to the model, overwrites the original model, and puts this new model into operation. However, one of the teams using the model has seen a decrease in performance and is asking to use the original model.
What critical error did your team make?

  1. They did not have data governance in place
  2. They did not practice model versioning and keep all versions of the model
  3. They did not have a model retraining pipeline that took into account models
  4. They did not practice model iteration and properly iterate on the model

Answer(s): B



Enhancing and cleaning data is an important action during which phase of CPMAI?

  1. Phase VI
  2. Phase I
  3. Phase V
  4. Phase III
  5. Phase II
  6. Phase IV

Answer(s): D



Your team is ready to operationalize the model they have been working on. It's a model that is meant to be used on an "edge device", specifically a mobile phone and the user may sometimes be in remote locations without regular access to the internet.
What's the most important thing to consider here?

  1. Make sure that you can use Generative AI solutions on an edge device
  2. Make sure the model lives in a hybrid environment
  3. Make sure the model is available over a cloud-based API
  4. Make sure the model lives on the edge device so it can be used regardless of internet connection

Answer(s): D



For AI projects the code and systems don't matter as much as the data. In fact, big data is what's powering much of this latest wave of AI.
What's most important for your company to consider around data?

  1. Because of almost-infinite storage and compute power, collect as much data as possible and deal with organizing it later.
  2. Collect enormous amounts of data - the more data the better.
  3. Understanding which algorithms are best for your data needs.
  4. Have team members that have experience, understanding of tools, and the ability to deal with massive volumes of data.

Answer(s): C



Using machine learning and other cognitive approaches to understand how to take past/existing behavior and predict future outcomes or help humans make decisions about future outcomes using insight learned from past behavior/interactions/data is a core part to which pattern(s) of AI?

  1. Goal Driven Systems
  2. Predictive Analytics & Decision Support and Patterns and Anomalies
  3. Recognition Pattern
  4. Predictive Analytics & Decision Support

Answer(s): D



As an organization building an AI solution for your current customers based in NYC, but with possible plans for future expansion, how should you handle worldwide AI laws and regulations?

  1. Make sure to follow relevant data, privacy, and other important laws both in the US and where you're likely to expand to in the coming year
  2. Make sure to follow relevant data, privacy, and other important laws as it pertains to NYC
  3. Make sure to follow relevant data, privacy, and other important laws as it pertains to the United
    States
  4. You're too small of an organization to be worried about laws at the moment

Answer(s): A



Your team is starting a new facial recognition project and you want to ensure that the project is being done with Trustworthy AI in mind.
At what phase of CPMAI would Trustworthy AI be considered?

  1. Phase I
  2. Phase II
  3. Phase III
  4. Phase IV
  5. Phase V
  6. Phase VI
  7. All phases
  8. None of the phases

Answer(s): G



You recently completed an image recognition project at your company that was focused on identifying different types of cars. You have now been assigned a new image recognition project that is focused on identifying different types of animals. You know you can shortcut model development by using a specific technique.
What is this technique called?

  1. Reinforcement Learning
  2. Generative AI
  3. Transfer Learning
  4. Pre-Trained Models

Answer(s): C



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