anomaly detection course
This course provides comprehensive training on anomaly detection techniques for real-time systems, covering dataset creation, feature engineering, model application, pipeline building, and ongoing monitoring to ensure effective and scalable detection.

from 4 to 360h flexible workload
valid certificate in your country
What will I learn?
This Anomaly Detection Course teaches you how to set clear detection objectives, create practical streaming datasets, and build strong real-time features for login and telemetry events. You'll evaluate rule-based, statistical, time-series, and machine learning approaches, then discover how to implement, oversee, and refine them using solid alerting, testing, and operational methods for dependable, low-noise detection on a large scale.
Elevify advantages
Develop skills
- Design streaming anomaly datasets: simulate attacks and realistic login events.
- Engineer real-time features: velocity, seasonality and per-user risk signals.
- Apply ML and rules: isolation forest, ARIMA, thresholds for fast anomalies.
- Build low-latency pipelines: Kafka, Flink, model APIs and alert routing.
- Tune, test and monitor detectors: replay traffic, metrics, drift and runbooks.
Suggested summary
Before starting, you can change the chapters and the workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.What our students are saying
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