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Explore anomaly detection methods for identifying unusual patterns in data. Learn to use machine learning algorithms for fraud detection and network security.
The language used throughout the course, in both instruction and assessments.
Anomaly detection is an important process in data mining that pinpoints complex, non-conforming patterns and outliers in a specific dataset. The process can identify events that deviate from the normal behavior expected from that dataset. The process can pick out everything from small software or hardware errors or glitches and hacks to serious machine vulnerabilities and critical zero-day attacks. ‎
It’s important to learn about anomaly detection if you plan to work in the field of machine learning and artificial intelligence (AI). Anomaly detection is a critical security tool that can identify significant fraud, network intrusions, and other events that can substantially disrupt a business or entire industry’s technological delivery system.‎
The types of jobs you can get by learning about anomaly detection can be found in all types of fields, including banking, financial services, insurance, retail, manufacturing, IT, government and defense, and health care. You might study anomaly detection to become a data scientist, big data engineer, machine learning developer, or fraud detection analyst within those fields. Studying the subject can open up opportunities for you in many companies that need to have data sources monitored for potential security threats and attacks. If you study anomaly detection, you also may be able to find a career in companies that need forensic accountants and fraud detection engineers to uncover unusual and sometimes suspicious activities.‎
Online courses can help you learn anomaly detection by giving you a better grasp of the broad subject of machine learning, including deep learning. Learning about anomaly detection online may give you the cutting-edge skills to teach you to build an anomaly detection model using deep learning and advanced technology such as Keras API with Tensorflow 2. You also may be able to learn how to create interactive charts and plots using Plotly Python and Seaborn for data visualization.‎
Online Anomaly Detection courses offer a convenient and flexible way to enhance your existing knowledge or learn new Anomaly Detection skills. With a wide range of Anomaly Detection classes, you can conveniently learn at your own pace to advance your Anomaly Detection career.‎
When looking to enhance your workforce's skills in Anomaly Detection, it's crucial to select a course that aligns with their current abilities and learning objectives. Our Skills Dashboard is an invaluable tool for identifying skill gaps and choosing the most appropriate course for effective upskilling. For a comprehensive understanding of how our courses can benefit your employees, explore the enterprise solutions we offer. Discover more about our tailored programs at Coursera for Business here.‎