6.4 Explain AI (generative and Predictive) and Machine Learning in Network Operations 200-301 Practice Questions (Page 6)

Questions 26–30

1. 26foundation · easy

   A network operations team wants to anticipate when a core switch might run out of capacity based on historical utilization trends. Which type of AI is best suited for this task?

   • APredictive AI
   • BComputer vision
   • CGenerative AI
   • DReinforcement learning
   Reveal Solution Discussion Select an answer first
2. 27foundation · easy

   What is the primary input for a predictive AI model used to forecast network traffic patterns?

   • AHistorical network telemetry data
   • BVendor documentation
   • CReal-time packet captures
   • DConfiguration management database (CMDB) entries
   Reveal Solution Discussion Select an answer first
4. 28foundation · easy

   What is a key limitation of using AI/ML models in network operations?

   • AThey always produce deterministic outputs for the same input.
   • BThey are only useful for security-related tasks.
   • CThey require high-quality, representative training data to produce accurate results.
   • DThey eliminate the need for human oversight entirely.
   Reveal Solution Discussion Select an answer first
5. 29application · medium

   A network team has a large dataset of NetFlow records but no labels indicating which flows are malicious. They want to identify unusual traffic patterns that might indicate a security threat. Which machine learning approach is most appropriate?

   • ASupervised learning with a labeled dataset of known attacks
   • BUnsupervised learning to cluster flows and detect outliers
   • CGenerative AI to create a report of all flows
   • DReinforcement learning to adjust firewall rules in real time
   Reveal Solution Discussion Select an answer first
6. 30expert · hard

   A network team wants to classify network traffic as either 'video conferencing' or 'web browsing' to apply QoS policies. They have a dataset of flows with labels. However, the dataset is imbalanced, with far more web browsing flows than video conferencing flows. What is the best approach?

   • AUse unsupervised learning to cluster the flows
   • BUse supervised learning with techniques to handle class imbalance, such as resampling
   • CUse reinforcement learning to adjust QoS policies
   • DUse the imbalanced dataset as-is to train the model
   Reveal Solution Discussion Select an answer first