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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Ce que vous apprendrez
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.
Compétences que vous acquerrez
- Catégorie : Microsoft Azure
- Catégorie : Data Integration
- Catégorie : Query Languages
- Catégorie : Scalability
- Catégorie : Process Optimization
- Catégorie : Data Analysis
- Catégorie : Anomaly Detection
- Catégorie : Generative AI
- Catégorie : User Feedback
- Catégorie : Application Performance Management
- Catégorie : Time Series Analysis and Forecasting
- Catégorie : Site Reliability Engineering
Détails à connaître
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Il y a 3 modules dans ce cours
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.
Inclus
8 lectures
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.
Inclus
7 lectures
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.
Inclus
8 lectures1 devoir
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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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