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Juniper JN0-253 Exam Overview:

Certification Vendor:Juniper Networks
Exam Name:Juniper Networks Certified Associate - Mist AI (JNCIA-MistAI) JN0-253
Exam Number:JN0-253
Related Certifications:JNCIS-ENT
JNCIA-Junos
Exam Format:Multiple-choice, Scenarios-based questions
Certificate Validity Period:3 years
Available Languages:English
Exam Price:$200 USD
Exam Duration:90 minutes
Recommended Training:Juniper Networks Training & Certification
Juniper Mist AI Official Training
Exam Registration:Juniper Certification Portal
Pearson VUE Juniper Exams
Sample Questions:Juniper JN0-253 Sample Questions
Exam Way:Online proctored or test center (Pearson VUE)
Pre Condition:No formal prerequisites required; basic networking knowledge recommended
Official Syllabus URL:https://www.juniper.net/us/en/training/certification/certification-tracks/mist-ai.html

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Juniper JN0-253 Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 2
  • Juniper Mist Cloud Operations: This domain covers three API types (RESTful, WebSocket, Webhook) for programmatic integration, plus support resources including ticketing systems and documentation.
Topic 3
  • 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.

Juniper Mist AI, Associate (JNCIA-MistAI) Sample Questions (Q74-Q79):

NEW QUESTION # 74
What is the sampling method used in supervised learning?

Answer: A

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 # 75
Which statement is true about Radio Resource Management (RRM)?

Answer: C

Explanation:
Juniper Mist Radio Resource Management (RRM) has a global optimization system that automatically evaluates the RF environment and optimizes radio settings once every 24 hours, ensuring balanced performance across the wireless network.


NEW QUESTION # 76
Which two statements are correct about the Juniper Mist "Application Health" SLE? (Choose two.)

Answer: B,C

Explanation:
The Application Health SLE tracks the performance of specific, often business-critical, cloud applications (such as Office 365, Zoom, or Salesforce) from the client's perspective, helping administrators determine whether performance issues stem from the local network or from the application/internet path beyond the network's control.


NEW QUESTION # 77
An AP is connected to your wired network but is not claimed to your organization. Which type of AP would be a possible security threat in this scenario?

Answer: A

Explanation:
Types of APs and Security Threats:
Understanding different types of access points and their potential security threats.
Access Point Types:
Neighbor AP: An access point that belongs to a neighboring network and is not necessarily a security threat.
Rogue AP: An unauthorized access point connected to the wired network, posing a significant security threat.
Spoofed AP: An access point that mimics a legitimate one, but typically does not involve being connected to the network.
Honeypot AP: An access point set up to lure attackers, not necessarily a threat unless used maliciously.
Identifying the Threat:
An AP connected to your wired network but not claimed to your organization is considered a rogue AP and poses a security threat.


NEW QUESTION # 78
Which two statements about WLAN templates are correct? (Choose two.)

Answer: A,D

Explanation:
WLAN Templates Overview: WLAN templates in Mist AI are used to standardize and manage wireless configurations across multiple locations and devices. They help in maintaining consistent wireless settings and policies throughout the network.
Deployment to the Whole Organization: WLAN templates can indeed be deployed at the organization level. This allows the configurations defined in the template to be applied across all sites and access points within the organization. This approach simplifies the management and ensures uniformity across the network(Juniper Networks).
Deployment to a Certain Site: WLAN templates can also be applied to specific sites. This is useful for organizations with multiple sites having unique wireless requirements. By applying templates at the site level, administrators can tailor configurations to meet local needs while still maintaining control through central management.


NEW QUESTION # 79
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