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| Section | Objectives |
|---|---|
| Topic 1: Juniper Mist Monitoring and Analytics | - Performance dashboards - Data-driven insights - User experience metrics |
| Topic 2: Marvis Virtual Network Assistant AI | - AI-driven insights - Troubleshooting capabilities |
| Topic 3: Juniper Mist Configuration Basics | - Initial configurations - Advanced configurations - Cloud accounts concepts and functionality |
| Topic 4: Juniper Mist Cloud Fundamentals | - Juniper Mist cloud capabilities and use cases - Machine learning - AI concepts - Benefits of using cloud-based management |
| Topic 5: Juniper Mist Network Operations and Management | - Wired network management and operations features - Wireless network management and operations features |
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NEW QUESTION # 143
Which machine learning method uses unlabeled data sets?
Answer: B
Explanation:
InJuniper Mist AI, variousmachine learning (ML)techniques are applied across the platform to analyze network telemetry and improve performance insights. Among these,unsupervised learningplays a critical role in identifying patterns, trends, and anomalies in unlabeled datasets-data that has not been pre-classified or annotated.
According to theJuniper Mist AI and Machine Learning Overview:
"Unsupervised learning enables Mist AI to automatically detect abnormal patterns or clusters in large volumes of unlabeled network data, allowing the system to identify anomalies and optimize network behavior without human labeling." This method allows Mist AI to autonomously recognize deviations in user experience, traffic behavior, or radio performance without prior definitions, helping to enhance predictive analytics and anomaly detection.
By contrast:
* Supervised learningrequires labeled training data.
* Reinforcement learninglearns through trial-and-error feedback loops.
* Cognitive learningis not a formal ML category-it refers to human-inspired reasoning.
Therefore, the correct answer isD. Unsupervised learning.
References:- Juniper Mist AI and Machine Learning Overview- Juniper Mist Cloud Architecture and AI Engine Guide- Juniper Mist Predictive Analytics and Correlation Engine (PACE) Documentation
NEW QUESTION # 144
Which type of machine learning does Radio Resource Management (RRM) use?
Answer: C
Explanation:
TheAI-driven Radio Resource Management (RRM)system inJuniper Mist Wireless Assuranceemploys reinforcement learningto continuously optimize wireless radio parameters such as channel selection, transmit power, and channel width.
According to theJuniper Mist Wireless Assurance and AI-Driven RRM Guide:
"The RRM system leverages reinforcement learning techniques to dynamically adjust radio configurations based on environmental conditions, user density, and interference patterns." Reinforcement learning enables the Mist AI system to make decisions by continuously evaluating the outcome of past configurations and improving future adjustments. This ensures that Mist RRM can autonomously optimize RF conditions for coverage and capacity without manual intervention.
Therefore, the correct answer isC. Reinforcement learning.
References:- Juniper Mist Wireless Assurance and AI-Driven RRM Guide- Juniper Mist AI and Machine Learning Architecture Documentation- Juniper Mist Cloud Operations and Optimization Overview
NEW QUESTION # 145
Which statement is correct about the Juniper Mist Cloud architecture?
Answer: D
Explanation:
The Juniper Mist Cloud is built on a modern microservices-based architecture hosted in the public cloud, providing horizontal scalability, high availability, and resiliency. This cloud-native, controller-less architecture also exposes a comprehensive set of open APIs, enabling integration with third-party systems and custom applications.
NEW QUESTION # 146
How are Mist Alerts sent?
Answer: A
NEW QUESTION # 147
What are two components of WiFi Management and Assurance? (Choose two.)
Answer: A,C
Explanation:
Dynamic Packet Capture and Radio Resource Management (RRM) are two key components of WiFi Management and Assurance in Juniper Mist. According to official documentation: "Dynamic packet capture allows capturing wireless packets between clients and an access point to diagnose root-cause wireless issues.
For example, when a major issue is detected, such as an authorization failure, packet captures facilitate quick troubleshooting and root-cause analysis." RRM, driven by Mist's AI, proactively analyzes network conditions and client experiences to automatically adjust channel and power settings for optimal performance: "AI- driven RRM uses data science and cumulative SLE performance to learn and optimize radio settings, helping RF planning to continue to improve and adapt in the changing environments..." Marvis Actions is an AI-powered troubleshooting feature, but it is a separate component enabled by the Marvis subscription, not by base WiFi Management and Assurance. Wayfinding is part of the vBLE Engagement or location services.
Reference:Juniper Mist Wi-Fi Assurance | UK&I , Mist Management Guide , Platform Wi-Fi Assurance - NetworkScreen.com
NEW QUESTION # 148
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