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AI-900 Practice Question: 'customer churn prediction' as an AI workload and…
This AI-900 practice question tests your understanding of 'customer churn prediction' as an ai workload and…. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
What is 'customer churn prediction' as an AI workload and what ML type does it use?
Answer choices
Why each option matters
Good practice is not just finding the correct option. The wrong answers often show the exact trap the exam wants you to fall into.
A
Distractor review
Detecting when a customer has already churned based on their last login date
Detecting past churn is rule-based logic — churn prediction uses ML to identify at-risk customers before they leave.
B
Distractor review
Using NLP to understand why customers write negative reviews before leaving
Negative review analysis is sentiment + topic modelling — churn prediction uses behavioural and transactional features, not text.
C
Distractor review
Analysing customer complaints to identify the root cause of service dissatisfaction
Root cause analysis of complaints is analytics/NLP — churn prediction uses ML to forecast which customers will leave.
D
Best answer
Using supervised classification to predict which customers are likely to cancel or become inactive
Churn prediction trains on labelled historical data (churned/retained) — enabling proactive retention targeting of high-risk customers.
Common exam trap
Common exam trap: NAT rules depend on direction and matching traffic
NAT is not only about the public address. The inside/outside interface roles and the ACL or rule that matches traffic are just as important.
Technical deep dive
How to think about this question
NAT questions usually test address translation, overload/PAT behaviour, static mappings and whether the right traffic is being translated. Read the interface direction and address terms carefully.
KKey Concepts to Remember
- Static NAT maps one inside address to one outside address.
- PAT allows many inside hosts to share one public address using ports.
- Inside local and inside global describe the private and translated addresses.
- NAT ACLs identify traffic for translation, not always security filtering.
TExam Day Tips
- Identify inside and outside interfaces first.
- Check whether the scenario needs static NAT, dynamic NAT or PAT.
- Do not confuse NAT matching ACLs with normal packet-filtering intent.
Key takeaway
NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.
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Question 5
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Question 6
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FAQ
Questions learners often ask
What does this AI-900 question test?
Static NAT maps one inside address to one outside address.
What is the correct answer to this question?
The correct answer is: Using supervised classification to predict which customers are likely to cancel or become inactive — Customer churn prediction forecasts which customers are likely to cancel their subscription, switch providers, or become inactive. It uses supervised classification: labelling historical customers as churned or retained, training a model on their features (usage patterns, support interactions, payment history, demographics), and scoring current customers for churn risk. High-risk customers can then be targeted with retention campaigns.
What should I do if I get this AI-900 question wrong?
Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related AI-900 NAT questions on configuration and troubleshooting.
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