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Juniper Mist AI, Associate (JNCIA-MistAI) Sample Questions (Q101-Q106):

NEW QUESTION # 101
How does Mist determine the location of clients in an indoor setting?

Answer: D

Explanation:
Mist builds location from "Probability Surfaces" not triangulation. The more directional RSSI beam information your client hears, the more data for the location engine to work with creating the probability surfaces, which provides the best possible location accuracy with sub second latency.


NEW QUESTION # 102
Which two statements are correct about the Juniper Mist vBLE Asset Visibility mode? (Choose two.)

Answer: A,D

Explanation:
Juniper Mist'svirtual Bluetooth Low Energy (vBLE)technology is designed to deliverprecise indoor location servicesusing cloud-managed access points equipped with integrated BLE antenna arrays. The system supports multiple operational modes, includingEngagement Mode(for mobile app interactions) and Asset Visibility Mode(for BLE tag tracking).
According to theJuniper Mist Location Services Documentation, inAsset Visibility Mode, the vBLE antenna functions primarily inreceive modeto detect and process signals emitted fromBLE asset tags. These tags periodically transmit Bluetooth "chirps" that are received by multiple APs. Mist Cloud then usesangle-of- arrival (AoA)andRSSI triangulation algorithmsto determine the exact location of the asset within the facility.
The documentation specifies:
"In Asset Visibility Mode, the vBLE antenna operates in receive mode and listens for BLE tag beacons (chirps). The system triangulates these signals to calculate the real-time location of tracked assets." Conversely,Engagement Modeis the configuration in which vBLE operates intransmit modeto interact with mobile devices running the Mist SDK - which corresponds to location-based engagement or proximity notifications.
Thus, the correct answers are:
* A. The vBLE antenna is in the receive mode
* B. The vBLE antenna tracks chirps from BLE tags
References:- Juniper Mist Location-Based Services Configuration Guide- Juniper Mist vBLE Architecture and Operation Modes Documentation- Juniper Mist Cloud Location Services Technical Overview


NEW QUESTION # 103
What are the principal types of machine learning for AI agents?

Answer: B

Explanation:
In theJuniper Mist AI ecosystem, the intelligence behind Mist's automation and insight generation is driven bymachine learning (ML)andartificial intelligence (AI)models. These models enable Mist AI to identify trends, predict network issues, and automate remediation through theMarvis Virtual Network Assistant (VNA).
According to theJuniper Mist AI and Machine Learning Overview, Mist AI utilizes several core ML paradigms:
"Mist AI leverages supervised, unsupervised, reinforcement, and deep learning models to interpret telemetry data, recognize behavioral patterns, and make predictive adjustments for network optimization."
* Supervised Learning- Uses labeled data for training, allowing Mist AI to identify known issues (e.g., DHCP failures or high latency).
* Unsupervised Learning- Detects anomalies or patterns in unlabeled datasets (e.g., identifying abnormal client behavior).
* Reinforcement Learning- Continuously improves network performance by using feedback from outcomes of previous actions.
* Deep Learning- Employs neural network models for complex pattern recognition and predictive analytics.
These combined learning approaches enable Mist AI to evolve autonomously and maintain accuracy through itsAI efficacy loop.
Therefore, the correct answer isD. Supervised, unsupervised, reinforcement, and deep learning.
References:- Juniper Mist AI and Machine Learning Overview- Juniper Mist AI Cloud Architecture and Predictive Analytics Guide- Juniper Mist Marvis Virtual Network Assistant Technical Documentation


NEW QUESTION # 104
Your manager asks you to configure all your remote Juniper EX Series switches to use Dynamic Port Configuration.
In this scenario, what are two criteria used for matching connected devices and assigning them their correct port and VLAN? (Choose two.)

Answer: B,C

Explanation:
Dynamic Port Configuration (DPC)inJuniper Mist Wired Assuranceallows EX Series switches to automatically assign port profiles, VLANs, and policies to connected devices based on their unique identifiers. This automation simplifies switch management and ensures consistent configurations across distributed networks.
According to theJuniper Mist Wired Assurance Configuration and Dynamic Port Management Guide:
"Dynamic Port Configuration matches connected endpoints using identifiers such as LLDP chassis ID and MAC address to assign the appropriate port profile or VLAN automatically."
* LLDP Chassis ID (C):Identifies the connected device by its LLDP advertisement, often representing a switch, phone, or AP.
* MAC Address (D):Provides unique device identification, ensuring precise port and VLAN assignment even when LLDP data is unavailable.
OptionsA (Serial Number)andB (IP Address)are not used for port configuration matching in DPC because they are not always available at the time of link establishment.
Therefore, the correct answers areC. LLDP Chassis IDandD. MAC Address.
References:- Juniper Mist Wired Assurance Configuration and Dynamic Port Management Guide- Juniper Mist Cloud Operations and Template Management Documentation- Juniper Mist EX Switch Dynamic Port Assignment Overview


NEW QUESTION # 105
Which two statements describe SLEs? (Choose two.)

Answer: A,D

Explanation:
InJuniper Mist AI,Service Level Expectations (SLEs)form the foundation ofWireless AssuranceandWired Assurance. They provide adata-driven, proactive methodto measure and maintain the quality of user experience, going beyond traditional device-centric monitoring.
According to theJuniper Mist AI Operations GuideandWireless Assurance Documentation, SLEs:
"Leverage machine learning and data science to deliver a proactive understanding of end-user experience and identify root causes of performance issues." Each SLE (such asTime to Connect,Roaming,Throughput,Coverage, andCapacity) is composed of classifiers, which break down performance metrics into measurable, root-cause categories. Examples include DHCP,DNS,Authentication, andSignal Qualityclassifiers.
This classifier-based structure enables Mist AI to automatically correlate problems and highlight the most probable cause of degradation-eliminating the need for manual troubleshooting or reactive analysis.
OptionsBandDare incorrect because SLEs arenot ad hoc toolsfor manual troubleshooting and donot simply list connected clients. Instead, they provide intelligent, AI-driven insights into user experience across the network.
Therefore, the correct statements are:
* A. SLEs use machine learning to provide a proactive approach to understanding the end-user experience.
* C. The metrics analyzed to meet specific SLE goals are categorized into classifiers.
References:- Juniper Mist Wireless Assurance and SLE Overview- Juniper Mist AI Operations and Analytics Guide- Juniper Mist Cloud Monitoring and SLE Classifier Documentation


NEW QUESTION # 106
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