Anomaly Detection using Artificial Intelligence
This course is designed for professionals who want to learn how to identify unusual patterns and outliers in data using machine learning algorithms.
Some of the key concepts covered in this course include:
supervised and unsupervised learning, data preprocessing, feature engineering, and model evaluation.
Through a combination of lectures, hands-on exercises, and projects, learners will gain practical experience in implementing anomaly detection techniques in real-world scenarios.
By the end of this course, learners will be able to develop their own anomaly detection models and apply them to various industries, such as finance, healthcare, and cybersecurity.
So, if you're interested in learning how to detect anomalies in data using AI, explore this course and start building your skills today!