PMI CPMAI Exam Practice Questions (P. 1)
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Question #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?
What critical error did your team make?
- AThey did not have data governance in place
- BThey did not practice model versioning and keep all versions of the model
- CThey did not have a model retraining pipeline that took into account models
- DThey did not practice model iteration and properly iterate on the model
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Question #2
Enhancing and cleaning data is an important action during which phase of CPMAI?
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Question #3
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?
What’s the most important thing to consider here?
- AMake sure that you can use Generative AI solutions on an edge device
- BMake sure the model lives in a hybrid environment
- CMake sure the model is available over a cloud-based API
- DMake sure the model lives on the edge device so it can be used regardless of internet connection
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Question #4
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?
- ABecause of almost-infinite storage and compute power, collect as much data as possible and deal with organizing it later.
- BCollect enormous amounts of data - the more data the better.
- CUnderstanding which algorithms are best for your data needs.
- DHave team members that have experience, understanding of tools, and the ability to deal with massive volumes of data.
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Question #5
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?
- AGoal Driven Systems
- BPredictive Analytics & Decision Support and Patterns and Anomalies
- CRecognition Pattern
- DPredictive Analytics & Decision Support
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