An outage rarely starts with a red dashboard-it starts as a small anomaly: a spike in latency, a surge in failures, or a subtle change in traffic. The faster you detect and respond, the less damage (and stress) you create. In this course, you’ll build an end-to-end anomaly detection and response loop on Azure. You’ll instrument an app with Application Insights, detect unusual behavior with Azure Monitor smart detection, dynamic thresholds, and KQL time-series functions, and then turn alerts into action using action groups and Logic Apps (with optional Azure Functions for custom remediation). You’ll learn a practical workflow: choose the right signal, set guardrails to reduce noise, enrich alerts with context, and automate a consistent response-notify the right channel, capture evidence, and trigger a safe mitigation step.
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您将学到什么
Apply machine learning techniques to detect anomalies in cybersecurity data such as logs, network traffic, and user behavior.
Automate incident response workflows by integrating AI-driven alerts with security orchestration tools.
Evaluate and fine-tune AI models to reduce false positives and improve real-time threat detection accuracy.
您将获得的技能
要了解的详细信息
添加到您的领英档案
1 项作业
了解顶级公司的员工如何掌握热门技能
该课程共有3个模块
This module introduces anomaly detection from the ground up: what an “anomaly” is, which signals to trust, and how Azure Monitor helps you detect unusual behavior without building a custom ML model. You’ll instrument a workload with Application Insights, explore built-in smart detection, and create your first alert rule using dynamic thresholds and action groups so the right people (or workflows) get notified fast.
涵盖的内容
8篇阅读材料
This module moves from “something is weird” to “what exactly changed and why.” You’ll learn KQL basics for beginners, then use time-series functions such as make-series and series_decompose_anomalies to detect spikes, dips, and seasonality-aware anomalies in logs. You’ll turn the query into a log alert rule and practice enriching alerts with anomaly scores, dimensions (region/role), and clear troubleshooting steps.
涵盖的内容
7篇阅读材料
This module turns detection into action. You’ll learn response patterns that are safe and repeatable, then wire Azure Monitor action groups to Logic Apps (and optionally Azure Functions) to notify, create tickets, capture evidence, and trigger a reversible mitigation. You’ll practice parsing the common alert schema so one automation can handle metric, log, and smart detection alerts.
涵盖的内容
8篇阅读材料1个作业
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To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.
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