What is an example of an anomaly that AI might detect?

A sudden increase in failed authentication attempts.

A regular backup occurring at the same time daily.

A user connecting from the same location every day.

A device that has been offline for a scheduled maintenance window.

A network engineer is troubleshooting a problem where users in a specific building are experiencing intermittent connectivity. They want to use Mist AI to correlate data from multiple sources and identify the root cause. What is the best way to do this?

Use Marvis to ask a natural language question about the issue.

Use AI for Troubleshooting to correlate data from access points, switches, and clients to identify the root cause.

Use AI for Anomaly Detection to identify unusual traffic patterns in the building.

Use AI for Analytics and Reporting to generate a report on connectivity issues.

How does predictive analytics help prevent network issues?

By only providing post-incident reports.

By alerting administrators to potential problems before they affect users.

By automatically rebooting devices when issues occur.

By requiring manual inspection of all devices.

What type of data does AI use to predict future network demands?

Historical usage trends and growth patterns.

Random samples of network traffic.

Only the number of support tickets.

Only the current number of connected devices.

How does AI assist in troubleshooting wired network issues?

By correlating switch telemetry with client and application data to pinpoint root causes.

By requiring administrators to manually check each port.

By only showing error logs without context.

By automatically replacing faulty switches.

Juniper NetworksCertified Associate, Mist AI

Domain 1Objective 1

AI Concepts JN0-253 Practice Questions (Page 10)

Part of the Juniper Mist Cloud Fundamentals domain, which makes up ~19% of our current practice bank. Juniper Networks does not publish an official question count, but from its 90-minute exam (~35–60 total, ~7–11 in this domain), expect 2–3 from this objective — we provide 59 practice questions to prepare you well beyond it. (estimate)

59questions here

12free pages

20concepts

20 Concepts in This Objective

AI Concepts Overview
Machine Learning in Mist
AI-Driven Insights
Marvis Virtual Network Assistant
AI for Wi-Fi Assurance
AI for Wired Assurance
AI for WAN Assurance
AI for Location Services
AI for Security
AI for User Engagement
AI for Service Desk
AI for IoT
AI for Analytics and Reporting
AI for Automation
AI for Troubleshooting
AI for Capacity Planning
AI for Performance Optimization
AI for Anomaly Detection
AI for Predictive Analytics
AI for Natural Language Processing

Questions 46–50

46foundation · easy
What is an example of an anomaly that AI might detect?
Select an answer first
47application · medium
A network engineer is troubleshooting a problem where users in a specific building are experiencing intermittent connectivity. They want to use Mist AI to correlate data from multiple sources and identify the root cause. What is the best way to do this?
Select an answer first
48foundation · easy
How does predictive analytics help prevent network issues?
Select an answer first
49foundation · easy
What type of data does AI use to predict future network demands?
Select an answer first
50foundation · easy
How does AI assist in troubleshooting wired network issues?
Select an answer first

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