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Juniper JN0-253 Exam Syllabus Topics:

Topic	Details
Topic 1	Location-based Services: This domain presents virtual Bluetooth Low Energy capabilities for asset tracking, visibility, and location-aware experiences that extend networking into physical space management.
Topic 2	Juniper Mist Configuration Basics: This domain addresses initial setup including user accounts, device onboarding, organizational structures, subscription licensing, certificate management, and automated provisioning with labels and policies.
Topic 3	Juniper Mist Cloud Fundamentals: This domain covers Juniper's cloud-native platform architecture, focusing on AI and machine learning capabilities for intelligent network management and real-world deployment scenarios.

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Juniper Mist AI, Associate (JNCIA-MistAI) Sample Questions (Q25-Q30):

NEW QUESTION # 25
How does Marvis detect a bad cable problem?

A. Marvis randomly performs cable tests on every cable in your network.
B. Marvis constantly sends ping packets to remote end hosts to determine whether there is a failure in the path.
C. Marvis randomly performs packet captures on various APs to find bad cables in your network.
D. Marvis analyzes metrics, such as interface errors, that match a bad cable pattern.

Answer: D

Explanation:
Marvis, the AI-driven Virtual Network Assistant inJuniper Mist, uses continuous telemetry analysis and AI correlation to identifybad cable conditions. It does this by examining interface-level statistics gathered from switches and access points throughWired Assurance.
According to theJuniper Mist Marvis Operations and Troubleshooting Guide:
"Marvis detects bad cable issues by analyzing telemetry patterns such as CRC errors, FCS errors, packet drops, and link flaps that collectively match a known cable fault signature." When such patterns are detected, Marvis automatically generates anAI Actionindicating aBad Cableissue and identifies whether the problem is with theportor thecable. This proactive detection allows administrators to replace faulty hardware before it impacts network users.
Options A, B, and C are incorrect because Marvis does not perform active pinging, random packet captures, or random cable testing. Its detection is entirelyAI and telemetry-based.
Therefore, the correct answer isD. Marvis analyzes metrics, such as interface errors, that match a bad cable pattern.
References:- Juniper Mist Marvis AI Operations Guide- Juniper Mist Wired Assurance and Telemetry Analytics Documentation- Juniper Mist AI Troubleshooting and Automation Overview

NEW QUESTION # 26
With which two external directory services does Juniper Mist Access Assurance integrate?
(Choose two.)

A. Okta Workforce Identity
B. Microsoft Azure Active Directory
C. RESTful API Fingerprinting
D. Meta Social Verify

Answer: A,B

Explanation:
Juniper Mist Access Assurance integrates with Microsoft Azure Active Directory for user authentication and policy enforcement.
It also integrates with Okta Workforce Identity to provide secure access control and identity management.

NEW QUESTION # 27
What are three features of Juniper Mist? (Choose three.)

A. Automatic feature updates
B. Asset tracking
C. Wireless Assurance
D. Perpetual Access Point licenses
E. Controller firmware updates

Answer: A,B,C

Explanation:
Wireless Assurance provides AI-driven monitoring and troubleshooting for Wi-Fi networks.
Asset tracking enables real-time location tracking of BLE-tagged devices.
Automatic feature updates ensure the Mist cloud and devices receive continuous improvements without manual intervention.

NEW QUESTION # 28
What is the sampling method used in supervised learning?

A. decision tree
B. regression
C. labeled dataset
D. random forest

Answer: C

Explanation:
The fundamental sampling method used in supervised learning is a labeled dataset. As described in Juniper Mist AI and machine learning application guides, supervised learning algorithms are trained using datasets in which each sample is paired with a known output (label). The model is fed examples comprising input data and the correct answer, learning patterns to map new inputs to their target outputs. While regression, decision tree, and random forest are techniques within supervised learning, the process fundamentally relies on having a labeled dataset for both training and validation phases. "Supervised machine learning models are built on labeled data, with each input paired to a target value or classification." This allows for accurate model training and evaluation.
Reference:Juniper Mist AI Explainable AI Reference , Machine Learning in Juniper Mist

NEW QUESTION # 29
Which statement is correct about the Juniper Mist "Time to Connect" SLE?

A. It cannot be broken down by classifier.
B. It measures how long it takes a client to physically walk to an access point.
C. It measures the time taken for a client to complete association, authentication, and DHCP/DNS steps to gain network access.
D. It only applies to wired clients.

Answer: C

Explanation:
The Time to Connect SLE measures the end-to-end time it takes for a wireless client to successfully complete the connection process, including association, authentication (such as
802.1X or PSK), and DHCP/DNS steps, providing insight into how quickly users can get onto the network.

NEW QUESTION # 30
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